IGI Global, 2023. — 326 p. — ISBN : 9781668469118. Social media platforms are one of the main generators of textual data where people around the world share their daily life experiences and information with online society. The social, personal, and professional lives of people on these social networking sites generate not only a huge amount of data but also open doors for...
IGI Global, 2023. — 326 p. — ISBN 978-1668469101. Social media platforms are one of the main generators of textual data where people around the world share their daily life experiences and information with online society. The social, personal, and professional lives of people on these social networking sites generate not only a huge amount of data but also open doors for...
Springer, 2023. — 287 p. This book is very beneficial for early researchers/faculty who want to work in Deep Learning and Machine Learning for the classification domain. It helps them study, formulate, and design their research goal by aligning the latest technologies studies’ image and data classifications. The early start-up can use it to work with product or prototype design...
ITexLi, 2020. — 103 p. — ISBN 1839628790 9781839628795 1839628804 9781839628801. This book examines Deep Learning (DL) applications and future trends in the field. It is a useful resource for researchers and students alike. Artificial Intelligence (AI) has attracted the attention of researchers and users alike and is taking an increasingly crucial role in our modern society....
Springer, 2022. — 271 p. — ISBN 978-3-030-75854-7. This book comprises theoretical foundations to deep learning, machine learning and computing system, deep learning algorithms, and various deep learning applications. The book discusses significant issues relating to deep learning in data analytics. Further in-depth reading can be done from the detailed bibliography presented...
Springer, 2022. — 271 p. — ISBN 978-3-030-75854-7. This book comprises theoretical foundations to deep learning, machine learning and computing system, deep learning algorithms, and various deep learning applications. The book discusses significant issues relating to deep learning in data analytics. Further in-depth reading can be done from the detailed bibliography presented...
Springer, 2020. — 200 p. — (Algorithms for Intelligent Systems). — ISBN: 9789811512155. This book covers deep-learning-based approaches for sentiment analysis, a relatively new, but fast-growing research area, which has significantly changed in the past few years. The book presents a collection of state-of-the-art approaches, focusing on the best-performing, cutting-edge...
Springer, 2018. — 512 p. — ISBN: 3319944622. This book covers both classical and modern models in deep learning. The chapters of this book span three categories: The basics of neural networks: Many traditional machine learning models can be understood as special cases of neural networks. An emphasis is placed in the first two chapters on understanding the relationship between...
Springer, 2018. — 512 p. — ISBN: 3319944622. This book covers both classical and modern models in deep learning. The chapters of this book span three categories: The basics of neural networks: Many traditional machine learning models can be understood as special cases of neural networks. An emphasis is placed in the first two chapters on understanding the relationship between...
2nd Edition. — Springer, 2023. — 541 p. — ISBN 978-3-031-29641-3. Neural networks were developed to simulate the human nervous system for Machine Learning tasks by treating the computational units in a learning model in a manner similar to human neurons. The grand vision of neural networks is to create artificial intelligence by building machines whose architecture simulates...
2nd Edition. — Springer, 2023. — 541 p. — ISBN 978-3-031-29642-0. Neural networks were developed to simulate the human nervous system for Machine Learning tasks by treating the computational units in a learning model in a manner similar to human neurons. The grand vision of neural networks is to create artificial intelligence by building machines whose architecture simulates...
2nd Edition. — Springer, 2023. — 541 p. — ISBN 978-3-031-29642-0. Neural networks were developed to simulate the human nervous system for Machine Learning tasks by treating the computational units in a learning model in a manner similar to human neurons. The grand vision of neural networks is to create artificial intelligence by building machines whose architecture simulates...
2nd Edition. — Springer, 2023. — 541 p. — ISBN 978-3-031-29642-0. Neural networks were developed to simulate the human nervous system for Machine Learning tasks by treating the computational units in a learning model in a manner similar to human neurons. The grand vision of neural networks is to create artificial intelligence by building machines whose architecture simulates...
Springer, 2021p. - 274p. - ISBN: 9783030656607 This book contributes to the progress towards intelligent transportation. It emphasizes new data management and machine learning approaches such as big data, deep learning and reinforcement learning. Deep learning and big data are very energetic and vital research topics of today’s technology. Road sensors, UAVs, GPS, CCTV and...
Springer, 2021p. - 274p. - ISBN: 9783030656607 This book contributes to the progress towards intelligent transportation. It emphasizes new data management and machine learning approaches such as big data, deep learning and reinforcement learning. Deep learning and big data are very energetic and vital research topics of today’s technology. Road sensors, UAVs, GPS, CCTV and...
AI Publishing, 2020. — 293 p. — ISBN13: 978-1-7347901-2-2. Artificial intelligence is the rage today! While you may find it difficult to understand the most recent advancements in AI, it simply boils down to two most celebrated developments: Machine Learning and Deep Learning. In 2020, Deep Learning is leagues ahead because of its supremacy when it comes to accuracy, especially...
AI Publishing, 2020. — 293 p. — ISBN13: 978-1-7347901-2-2. Artificial intelligence is the rage today! While you may find it difficult to understand the most recent advancements in AI, it simply boils down to two most celebrated developments: Machine Learning and Deep Learning. In 2020, Deep Learning is leagues ahead because of its supremacy when it comes to accuracy, especially...
AI Publishing, 2020. — 293 p. — ISBN13: 978-1-7347901-2-2. Artificial intelligence is the rage today! While you may find it difficult to understand the most recent advancements in AI, it simply boils down to two most celebrated developments: Machine Learning and Deep Learning. In 2020, Deep Learning is leagues ahead because of its supremacy when it comes to accuracy, especially...
AI Publishing LLC, 2020. — 293 p. — ISBN B08959G3H8. Artificial intelligence is the rage today! While you may find it difficult to understand the most recent advancements in AI, it simply boils down to two most celebrated developments: Machine Learning and Deep Learning. In 2020, Deep Learning is leagues ahead because of its supremacy when it comes to accuracy, especially when...
Apress, 2019. — 427 p. — ISBN: 978-1-4842-5176-8. Utilize this easy-to-follow beginner's guide to understand how deep learning can be applied to the task of anomaly detection. Using Keras and PyTorch in Python, the book focuses on how various deep learning models can be applied to semi-supervised and unsupervised anomaly detection tasks. This book begins with an explanation of...
Apress, 2019. — 416 p. — ISBN: 978-1-4842-5176-8. Utilize this easy-to-follow beginner's guide to understand how deep learning can be applied to the task of anomaly detection. Using Keras and PyTorch in Python, the book focuses on how various deep learning models can be applied to semi-supervised and unsupervised anomaly detection tasks. This book begins with an explanation of...
2nd Edition. — Apress Media LLC., 2024. — 527 р. — ISBN-13: 979-8-8688-0008-5. This beginner-oriented book will help you understand and perform anomaly detection by learning cutting-edge machine learning and deep learning techniques. This updated second edition focuses on supervised, semi-supervised, and unsupervised approaches to anomaly detection. Over the course of the book,...
2nd Edition. — Apress Media LLC., 2024. — 527 р. — ISBN-13: 979-8-8688-0008-5. This beginner-oriented book will help you understand and perform anomaly detection by learning cutting-edge machine learning and deep learning techniques. This updated second edition focuses on supervised, semi-supervised, and unsupervised approaches to anomaly detection. Over the course of the book,...
2nd Edition. — Apress Media LLC., 2024. — 527 р. — ISBN-13: 979-8-8688-0008-5. This beginner-oriented book will help you understand and perform anomaly detection by learning cutting-edge machine learning and deep learning techniques. This updated second edition focuses on supervised, semi-supervised, and unsupervised approaches to anomaly detection. Over the course of the book,...
Apress, 2019. — 390 p. — ISBN13: (electronic): 978-1-4842-5177-5. Utilize this easy-to-follow beginner’s guide to understand how deep learning can be applied to the task of anomaly detection. Using Keras and PyTorch in Python, the book focuses on how various deep learning models can be applied to semi-supervised and unsupervised anomaly detection tasks. This book begins with an...
Apress, 2019. — 390 p. — ISBN13: (electronic): 978-1-4842-5177-5. Utilize this easy-to-follow beginner’s guide to understand how deep learning can be applied to the task of anomaly detection. Using Keras and PyTorch in Python, the book focuses on how various deep learning models can be applied to semi-supervised and unsupervised anomaly detection tasks. This book begins with an...
Springer Cham, 2023. — 94 p. — (Synthesis Lectures on Engineering, Science, and Technology) — eBook ISBN: 978-3-031-38133-1. Explores different design aspects associated with each number system and their effects on DNN performance Discusses the most efficient number systems for DNNs hardware realization Describes various number systems and their usage for Deep Neural Network...
Springer Cham, 2023. — 94 p. — (Synthesis Lectures on Engineering, Science, and Technology) — eBook ISBN: 978-3-031-38133-1. Explores different design aspects associated with each number system and their effects on DNN performance Discusses the most efficient number systems for DNNs hardware realization Describes various number systems and their usage for Deep Neural Network...
Apress, 2020. — 356 p. — ISBN 9781484264300. Build deep learning and computer vision systems using Python, TensorFlow, Keras, OpenCV, and more, right within the familiar environment of Microsoft Windows. The book starts with an introduction to tools for deep learning and computer vision tasks followed by instructions to install, configure, and troubleshoot them. Here, you will...
Apress, 2020. — 356 p. — ISBN 9781484264300. Build deep learning and computer vision systems using Python, TensorFlow, Keras, OpenCV, and more, right within the familiar environment of Microsoft Windows. The book starts with an introduction to tools for deep learning and computer vision tasks followed by instructions to install, configure, and troubleshoot them. Here, you will...
Independently published, 2019. — 272 р. — ISBN: 978-1793223012. New 2019 Edition! Build Deeper is a complete and practical guide that can help you take the first few steps in deep learning. It will guide you step-by-step, from understanding the basic concepts, to building your first practical application. Deep Learning is the latest iteration of AI. Although the concept itself...
Independently published, 2019. — 272 р. — ISBN: 978-1793223012. New 2019 Edition! Build Deeper is a complete and practical guide that can help you take the first few steps in deep learning. It will guide you step-by-step, from understanding the basic concepts, to building your first practical application. Deep Learning is the latest iteration of AI. Although the concept itself...
KDimensions, 2022. — 236 p. Визуальное введение в глубокое обучение Deep Learning is the algorithm powering the current renaissance of Artificial Intelligence (AI). And the progress is not showing signs of slowing down. A McKinsey report estimates that by 2030, AI will potentially deliver $13 trillion to the global economy, or 16% of the world's current GDP. This opens up...
Morgan & Claypool Publishers , 2020. - 111p. - ISBN: 9781681739137 This book provides a short introduction and easy-to-follow implementation steps of deep learning using Google Cloud Platform. It also includes a practical case study that highlights the utilization of Python and related libraries for running a pre-trained deep learning model. In recent years, deep learning-based...
John Wiley & Sons, Inc., 2025. — 256 p. — ISBN 978-1-394-26927-3. Comprehensive, accessible introduction to deep learning for engineering tasks through Python programming, low-cost hardware, and freely available software Deep Learning on Embedded Systems is a comprehensive guide to the practical implementation of deep learning for engineering tasks through computers and...
John Wiley & Sons, Inc., 2025. — 256 p. — ISBN 978-1-394-26927-3. Comprehensive, accessible introduction to deep learning for engineering tasks through Python programming, low-cost hardware, and freely available software Deep Learning on Embedded Systems is a comprehensive guide to the practical implementation of deep learning for engineering tasks through computers and...
John Wiley & Sons, Inc., 2025. — 256 p. — ISBN 978-1-394-26927-3. Comprehensive, accessible introduction to deep learning for engineering tasks through Python programming, low-cost hardware, and freely available software Deep Learning on Embedded Systems is a comprehensive guide to the practical implementation of deep learning for engineering tasks through computers and...
Apress, 2018. — 343 p. Discover the potential applications, challenges, and opportunities of deep learning from a business perspective with technical examples. These applications include image recognition, segmentation and annotation, video processing and annotation, voice recognition, intelligent personal assistants, automated translation, and autonomous vehicles. An...
Apress, 2018. — 343 p. Discover the potential applications, challenges, and opportunities of deep learning from a business perspective with technical examples. These applications include image recognition, segmentation and annotation, video processing and annotation, voice recognition, intelligent personal assistants, automated translation, and autonomous vehicles. An...
Princeton: LN, 2023. — 227 p. Basic Setup and some math notions List of useful math facts Basics of Optimization Gradient descent (GD) Stochastic gradient descent (SGD) Accelerated Gradient Descent Running time: Learning Rates and Update Directions Convergence rates under smoothness conditions Correspondence of theory with practice Note on overparametrized linear regression and...
2nd ed. — Birmingham: Packt Publishing, 2020. — 512 p. — ISBN: 1838821651. Updated and revised second edition of the bestselling guide to advanced deep learning with TensorFlow 2 and Keras ! Key Features Explore the most advanced deep learning techniques that drive modern AI results. New coverage of unsupervised deep learning using mutual information, object detection, and...
2nd Edition. — Packt Publishing, 2020. — 503 p. — ISBN: 978-1-83882-165-4. Updated and revised second edition of the bestselling guide to advanced deep learning with TensorFlow 2 and Keras Advanced Deep Learning with TensorFlow 2 and Keras, Second Edition is a completely updated edition of the bestselling guide to the advanced deep learning techniques available today. Revised...
2nd Edition. — Packt Publishing, 2020. — 503 p. — ISBN: 978-1-83882-165-4. Updated and revised second edition of the bestselling guide to advanced deep learning with TensorFlow 2 and Keras Advanced Deep Learning with TensorFlow 2 and Keras, Second Edition is a completely updated edition of the bestselling guide to the advanced deep learning techniques available today. Revised...
2nd Edition. — Packt Publishing, 2020. — 503 p. — ISBN: 978-1-83882-165-4. Updated and revised second edition of the bestselling guide to advanced deep learning with TensorFlow 2 and Keras Advanced Deep Learning with TensorFlow 2 and Keras, Second Edition is a completely updated edition of the bestselling guide to the advanced deep learning techniques available today. Revised...
2nd Edition. — Packt Publishing, 2020. — 512 p. — ISBN: 978-1-83882-165-4. Code files only! Updated and revised second edition of the bestselling guide to advanced deep learning with TensorFlow 2 and Keras Advanced Deep Learning with TensorFlow 2 and Keras, Second Edition is a completely updated edition of the bestselling guide to the advanced deep learning techniques available...
2nd Edition. — Packt Publishing, 2020. — 512 p. — ISBN: 978-1-83882-165-4. Code files only! Updated and revised second edition of the bestselling guide to advanced deep learning with TensorFlow 2 and Keras Advanced Deep Learning with TensorFlow 2 and Keras, Second Edition is a completely updated edition of the bestselling guide to the advanced deep learning techniques available...
Packt Publishing, 2020. — 286 p. — ISBN: 978-1-78913-396-7. Work through practical recipes to learn how to automate complex machine learning and deep learning problems using Python. With artificial intelligence systems, we can develop goal-driven agents to automate problem-solving. This involves predicting and classifying the available data and training agents to execute tasks...
Packt Publishing, 2020. — 286 p. — ISBN: 978-1-78913-396-7. Work through practical recipes to learn how to automate complex machine learning and deep learning problems using Python. With artificial intelligence systems, we can develop goal-driven agents to automate problem-solving. This involves predicting and classifying the available data and training agents to execute tasks...
Packt Publishing, 2020. — 286 p. — ISBN: 978-1-78913-396-7. Code files only! Work through practical recipes to learn how to automate complex machine learning and deep learning problems using Python. With artificial intelligence systems, we can develop goal-driven agents to automate problem-solving. This involves predicting and classifying the available data and training agents...
Birmingham: Packt Publishing, 2020. — 472 p. — ISBN: 978-1839219856. Take a hands-on approach to understanding deep learning and build smart applications that can recognize images and interpret text ! Key Features Understand how to implement deep learning with TensorFlow and Keras . Learn the fundamentals of computer vision and image recognition . Study the architecture of...
Mirza Rahim Baig, Thomas V. Joseph, Nipun Sadvilkar, Mohan Kumar Silaparasetty, Anthony So. — Packt Publishing Ltd., July 2020. — 474 p. — ISBN: 978-1-83921-985-6. Take a hands-on approach to understanding deep learning and build smart applications that can recognize images and interpret text Are you fascinated by how deep learning powers intelligent applications such as...
Mirza Rahim Baig, Thomas V. Joseph, Nipun Sadvilkar, Mohan Kumar Silaparasetty, Anthony So. — Packt Publishing Ltd., July 2020. — 474 p. — ISBN: 978-1-83921-985-6. Take a hands-on approach to understanding deep learning and build smart applications that can recognize images and interpret text Are you fascinated by how deep learning powers intelligent applications such as...
Mirza Rahim Baig, Thomas V. Joseph, Nipun Sadvilkar, Mohan Kumar Silaparasetty, Anthony So. — Packt Publishing Ltd., July 2020. — 474 p. — ISBN: 978-1-83921-985-6. Take a hands-on approach to understanding deep learning and build smart applications that can recognize images and interpret text Are you fascinated by how deep learning powers intelligent applications such as...
Mirza Rahim Baig, Thomas V. Joseph, Nipun Sadvilkar, Mohan Kumar Silaparasetty, Anthony So. — Packt Publishing Ltd., July 2020. — 474 p. — ISBN: 978-1-83921-985-6. Code files only! Take a hands-on approach to understanding deep learning and build smart applications that can recognize images and interpret text Are you fascinated by how deep learning powers intelligent...
Mirza Rahim Baig, Thomas V. Joseph, Nipun Sadvilkar, Mohan Kumar Silaparasetty, Anthony So. — Packt Publishing Ltd., July 2020. — 474 p. — ISBN: 978-1-83921-985-6. Code files only! Take a hands-on approach to understanding deep learning and build smart applications that can recognize images and interpret text Are you fascinated by how deep learning powers intelligent...
Packt Publishing, 2017. — 330 p. — ISBN: 178712519X. Solve different problems in modelling deep neural networks using Python, Tensorflow, and Keras with this practical guide. Deep Learning is revolutionizing a wide range of industries. For many applications, deep learning has proven to outperform humans by making faster and more accurate predictions. This book provides a...
Packt Publishing, 2017. — 330 p. — ISBN: 178712519X. Solve different problems in modelling deep neural networks using Python, Tensorflow, and Keras with this practical guide. Deep Learning is revolutionizing a wide range of industries. For many applications, deep learning has proven to outperform humans by making faster and more accurate predictions. This book provides a...
Packt Publishing, 2017. — 330 p. — ISBN: 178712519X. Solve different problems in modelling deep neural networks using Python, Tensorflow, and Keras with this practical guide. Deep Learning is revolutionizing a wide range of industries. For many applications, deep learning has proven to outperform humans by making faster and more accurate predictions. This book provides a...
Packt Publishing, 2017. — 330 p. — ISBN: 178712519X. Solve different problems in modelling deep neural networks using Python, Tensorflow, and Keras with this practical guide. Deep Learning is revolutionizing a wide range of industries. For many applications, deep learning has proven to outperform humans by making faster and more accurate predictions. This book provides a...
Elsevier, 2021. — 307 p. Deep learning (DL) is a method of machine learning, running over artificial neural networks, that uses multiple layers to extract high-level features from large amounts of raw data. DL methods apply levels of learning to transform input data into more abstract and composite information. Handbook for Deep Learning in Biomedical Engineering: Techniques...
Balas Valentina Emilia, Roy Sanjiban Sekhar, Sharma Dharmendra, Samui Pijush. — Springer, 2019. — 380 p. — (Smart Innovation, Systems and Technologies). — ISBN: 978-3-030-11479-4 (eBook). This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image...
Balas Valentina Emilia, Roy Sanjiban Sekhar, Sharma Dharmendra, Samui Pijush. — Springer, 2019. — 380 p. — (Smart Innovation, Systems and Technologies). — ISBN: 978-3-030-11479-4 (eBook). This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image...
Balas Valentina Emilia, Roy Sanjiban Sekhar, Sharma Dharmendra, Samui Pijush. — Springer, 2019. — 380 p. — (Smart Innovation, Systems and Technologies). — ISBN: 978-3-030-11479-4 (eBook). This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image...
Springer, 2019. — 380 p. — (Smart Innovation, Systems and Technologies). — ISBN10: 3030114783, 13 978-3030114787. This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain-computer interfaces,...
Cambridge: Cambridge University Press, 2021. — 387 p. This is the first rigorous, self-contained treatment of the theory of deep learning. Starting with the foundations of the theory and building it up, this is essential reading for any scientists, instructors, and students interested in artificial intelligence and deep learning. It provides guidance on how to think about...
Wiley-Scrivener, 2023. — 255 p. Research into Deep Learning has come a long way across multiple domains, such as healthcare, marketing, banking, manufacturing, education, and so on. Notable applications within these domains are trending, like visual recognition, fraud detection, virtual assistance, NLP, etc. Deep Learning models are used to implement these applications. Those...
John Wiley & Sons, Inc., 2023. — 256 p. — eBook ISBN: 978-1-394-16777-7. This book thoroughly explains deep learning models and how to use Python programming to implement them in applications such as NLP, face detection, face recognition, face analysis, and virtual assistance (chatbot, machine translation, etc.). It provides hands-on guidance in using Python for implementing...
Unpublished, 2015. — 94 p. Deep learning is a framework for training and modelling neural networks which recently have surpassed all conventional methods in many learning tasks, prominently image and voice recognition. This thesis uses deep learning algorithms to forecast financial data. The deep learning framework is used to train a neural network. The deep neural network is a...
Birmingham: Packt Publishing, 2023. — 385 p. — ISBN 180324688X. Develop Bayesian Deep Learning models to help make your own applications more robust. Key Features Learn how advanced convolutions work. Learn to implement a convolution neural network. Learn advanced architectures using convolution neural networks. Apply Bayesian NN to decrease weighted distribution. Bayesian Deep...
IOP Publishing, 2022. — 267 p. — (IOP Series in Next Generation Computing). Artificial Intelligence (AI) is gaining traction in areas of social responsibility. From climate change to social polarization to epidemics, humankind has been seeking new solutions to these ever-present problems. Deep Learning (DL) techniques have increased in power in recent years, with algorithms...
IOP Publishing, 2022. — 267 p. — (IOP Series in Next Generation Computing). Artificial Intelligence (AI) is gaining traction in areas of social responsibility. From climate change to social polarization to epidemics, humankind has been seeking new solutions to these ever-present problems. Deep Learning (DL) techniques have increased in power in recent years, with algorithms...
Berlin: de Gruyter, 2023. — 134 p. The goal of this book is to provide a mathematical perspective on some key elements of the so-called Deep Neural Networks (DNNs). Much of the interest in Deep Learning has focused on the implementation of DNN-based algorithms. Our hope is that this compact textbook will offer a complementary point of view that emphasizes the underlying...
Packt Publishing, 2018. — 272 p. — ISBN: 1788837991. Dive deeper into neural networks and get your models trained, optimized with this quick reference guide. Deep learning has become an essential necessity to enter the world of artificial intelligence. With this book deep learning techniques will become more accessible, practical, and relevant to practicing data scientists. It...
Packt Publishing, 2018. — 272 p. — ISBN: 1788837991. Dive deeper into neural networks and get your models trained, optimized with this quick reference guide. Deep learning has become an essential necessity to enter the world of artificial intelligence. With this book deep learning techniques will become more accessible, practical, and relevant to practicing data scientists. It...
Packt Publishing, 2018. — 272 p. — ISBN: 1788837991. Dive deeper into neural networks and get your models trained, optimized with this quick reference guide. Deep learning has become an essential necessity to enter the world of artificial intelligence. With this book deep learning techniques will become more accessible, practical, and relevant to practicing data scientists. It...
Apress, 2017. — 227 p. — ISBN: 978-1484227336. Understand deep learning, the nuances of its different models, and where these models can be applied. The abundance of data and demand for superior products/services have driven the development of advanced computer science techniques, among them image and speech recognition. Introduction to Deep Learning Using R provides a...
Apress, 2017. — 227 p. — ISBN: 978-1484227336. Understand deep learning, the nuances of its different models, and where these models can be applied. The abundance of data and demand for superior products/services have driven the development of advanced computer science techniques, among them image and speech recognition. Introduction to Deep Learning Using R provides a...
Apress, 2017. — 227 p. — ISBN: 978-1484227336. Code files only! Understand deep learning, the nuances of its different models, and where these models can be applied. The abundance of data and demand for superior products/services have driven the development of advanced computer science techniques, among them image and speech recognition. Introduction to Deep Learning Using R...
Apress Berkeley, 2024. — 364 p. — eBook ISBN 979-8-8688-1035-0. Provides explanations on sequence models and their analysis using various datasets. Covers generative models and transformers, demonstrating their applications. Provides hands-on projects that guide you in understanding the processes of model creation, fine-tuning, and testing. This book discusses deep learning,...
Apress, 2024. - 372 p. - ISBN 9798868810343. This book discusses deep learning, from its fundamental principles to its practical applications, with hands-on exercises and coding. It focuses on deep learning techniques and shows how to apply them across a wide range of practical scenarios. The book begins with an introduction to the core concepts of deep learning. It delves into...
Apress Media LLC, 2024. — 384 p. — ISBN-13: 979-8-8688-1034-3. This book discusses deep learning, from its fundamental principles to its practical applications, with hands-on exercises and coding. It focuses on deep learning techniques and shows how to apply them across a wide range of practical scenarios. The book begins with an introduction to the core concepts of deep...
Apress Media LLC, 2024. — 384 p. — ISBN-13: 979-8-8688-1034-3. This book discusses deep learning, from its fundamental principles to its practical applications, with hands-on exercises and coding. It focuses on deep learning techniques and shows how to apply them across a wide range of practical scenarios. The book begins with an introduction to the core concepts of deep...
Siddhartha Bhattacharyya, Vaclav Snasel, Aboul Ella Hassanien, Satadal Saha, B. K. Tripathy (Eds.). — Walter de Gruyter, 2020. — 179 p. — ISBN: 978-3110670790. This book focuses on the fundamentals of deep learning along with reporting on the current state-of-art research on deep learning. In addition, it provides an insight of deep neural networks in action with illustrative...
Siddhartha Bhattacharyya, Vaclav Snasel, Aboul Ella Hassanien, Satadal Saha, B. K. Tripathy (Eds.). — Walter de Gruyter, 2020. — 179 p. — ISBN: 978-3110670790. This book focuses on the fundamentals of deep learning along with reporting on the current state-of-art research on deep learning. In addition, it provides an insight of deep neural networks in action with illustrative...
Siddhartha Bhattacharyya, Vaclav Snasel, Aboul Ella Hassanien, Satadal Saha, B. K. Tripathy (Eds.). — Walter de Gruyter, 2020. — 179 p. — ISBN: 978-3110670790. This book focuses on the fundamentals of deep learning along with reporting on the current state-of-art research on deep learning. In addition, it provides an insight of deep neural networks in action with illustrative...
Siddhartha Bhattacharyya, Vaclav Snasel, Aboul Ella Hassanien, Satadal Saha, B. K. Tripathy (Eds.). — Walter de Gruyter, 2020. — 179 p. — ISBN: 978-3110670790. This book focuses on the fundamentals of deep learning along with reporting on the current state-of-art research on deep learning. In addition, it provides an insight of deep neural networks in action with illustrative...
Siddhartha Bhattacharyya, Vaclav Snasel, Aboul Ella Hassanien, Satadal Saha, B. K. Tripathy (Eds.). — Walter de Gruyter, 2020. — 179 p. — ISBN: 978-3110670790. This book focuses on the fundamentals of deep learning along with reporting on the current state-of-art research on deep learning. In addition, it provides an insight of deep neural networks in action with illustrative...
Boca Raton: CRC Press, 2024. — 313 p. Deep Learning for Multimedia Processing Applications is a comprehensive guide that explores the revolutionary impact of Deep Learning techniques in the field of multimedia processing. Written for a wide range of readers, from students to professionals, this book offers a concise and accessible overview of the application of Deep Learning in...
Boca Raton: CRC Press, 2023. — 481 p. Deep Learning for Multimedia Processing Applications is a comprehensive guide that explores the revolutionary impact of deep learning techniques in the field of multimedia processing. Written for a wide range of readers, from students to professionals, this book offers a concise and accessible overview of the application of deep learning in...
Springer, 2023. — 655 p. — ISBN 3031454677. This book offers a comprehensive introduction to the central ideas that underpin deep learning. It is intended both for newcomers to machine learning and for those already experienced in the field . Covering key concepts relating to contemporary architectures and techniques, this essential book equips readers with a robust foundation...
Springer, 2024. — 656 p. This book offers a comprehensive introduction to the central ideas that underpin Deep Learning. It is intended both for newcomers to machine learning and for those already experienced in the field. Covering key concepts relating to contemporary architectures and techniques, this essential book equips readers with a robust foundation for potential future...
Packt Publishing, 2019. — 372 p. — ISBN 978-1-83855-029-5. Explore deep neural network architectures and their application areas to overcome your NLP issues Key Features Get to grips with the basic building blocks of natural language processing Understand how to select the most suitable deep neural network to solve your NLP problems Explore convolutional and recurrent neural...
IGI Global, 2020. -351p. - 9781799827917 Interest in big data has swelled within the scholarly community as has increased attention to the internet of things (IoT). Algorithms are constructed in order to parse and analyze all this data to facilitate the exchange of information. However, big data has suffered from problems in connectivity, scalability, and privacy since its...
IGI Global, 2020. -351p. - 9781799827917 Interest in big data has swelled within the scholarly community as has increased attention to the internet of things (IoT). Algorithms are constructed in order to parse and analyze all this data to facilitate the exchange of information. However, big data has suffered from problems in connectivity, scalability, and privacy since its...
Packt Publishing, 2017. — 300 p. — ISBN: 978-1-78646-582-5. Develop deep neural networks in Theano with practical code examples for image classification, machine translation, reinforcement agents, or generative models. This book offers a complete overview of Deep Learning with Theano, a Python-based library that makes optimizing numerical expressions and deep learning models...
Packt Publishing, 2017. — 300 p. — ISBN: 978-1-78646-582-5. Develop deep neural networks in Theano with practical code examples for image classification, machine translation, reinforcement agents, or generative models. This book offers a complete overview of Deep Learning with Theano, a Python-based library that makes optimizing numerical expressions and deep learning models...
Packt Publishing, 2017. — 300 p. — ISBN: 978-1-78646-582-5. True PDF Develop deep neural networks in Theano with practical code examples for image classification, machine translation, reinforcement agents, or generative models. This book offers a complete overview of Deep Learning with Theano, a Python-based library that makes optimizing numerical expressions and deep learning...
Packt Publishing, 2017. — 300 p. — ISBN: 978-1-78646-582-5. Develop deep neural networks in Theano with practical code examples for image classification, machine translation, reinforcement agents, or generative models. This book offers a complete overview of Deep Learning with Theano, a Python-based library that makes optimizing numerical expressions and deep learning models...
Bleeding Edge Press, 2018. — 243 p. This book covers the crossroads of web development and deep learning. Both technologies are beginning to meet, and this honeymoon will produce new fantastic applications that you cannot even imagine yet. In this book you will see how to use the main JavaScript deep learning frameworks and web programming in the browser with the capture of...
CreateSpace Independent Publishing Platform, 2018. — 245 p. — ISBN10: 1724716417, 13 978-1724716415. About the book: In Computer Sciences there is currently a gold rush mood due to a new field called "Deep Learning". But what is Deep Learning? This book is an introduction to Neural Networks and the most important Deep Learning model - the Convolutional Neural Network model...
Springer, 2020. — 303 p. — (Computational Synthesis and Creative Systems). — ISBN: 978-3-319-70162-2. This book is a survey and analysis of how deep learning can be used to generate musical content. The authors offer a comprehensive presentation of the foundations of deep learning techniques for music generation. They also develop a conceptual framework used to classify and...
Manning Publications Co., 2025. — 392 p. — ISBN: 978-1617299056. A hands-on guide to powerful graph-based deep learning models. In Graph Neural Networks in Action, you will learn how to: Train and deploy a graph neural network Generate node embeddings Use GNNs at scale for very large datasets Build a graph data pipeline Create a graph data schema Understand the taxonomy of GNNs...
Manning Publications Co., 2025. — 392 p. — ISBN: 978-1617299056. A hands-on guide to powerful graph-based deep learning models. In Graph Neural Networks in Action, you will learn how to: Train and deploy a graph neural network Generate node embeddings Use GNNs at scale for very large datasets Build a graph data pipeline Create a graph data schema Understand the taxonomy of GNNs...
Manning Publications Co., 2025. — 392 p. — ISBN: 978-1617299056. A hands-on guide to powerful graph-based deep learning models. In Graph Neural Networks in Action, you will learn how to: Train and deploy a graph neural network Generate node embeddings Use GNNs at scale for very large datasets Build a graph data pipeline Create a graph data schema Understand the taxonomy of GNNs...
Manning Publications Co., 2025. — 392 p. — ISBN: 978-1617299056. A hands-on guide to powerful graph-based deep learning models. In Graph Neural Networks in Action, you will learn how to: Train and deploy a graph neural network Generate node embeddings Use GNNs at scale for very large datasets Build a graph data pipeline Create a graph data schema Understand the taxonomy of GNNs...
Machine Learning Mastery, 2018. — 575 p. Deep learning neural networks have become easy to define and fit, but are still hard to configure. Discover exactly how to improve the performance of deep learning neural network models on your predictive modeling projects. With clear explanations, standard Python libraries, and step-by-step tutorial lessons, you’ll discover how to...
Edition 1.4. — 2018. — 574 p. Introduction Foundations Promise of Deep Learning for Time Series Forecasting Time Series Forecasting Convolutional Neural Networks for Time Series Recurrent Neural Networks for Time Series Promise of Deep Learning Extensions Further Reading Taxonomy of Time Series Forecasting Problems Framework Overview Inputs vs. Outputs Endogenous vs. Exogenous...
Machine Learning Mastery Pty. Ltd. — 255 p. Deep learning is the most interesting and powerful machine learning technique right now. Top deep learning libraries are available on the Python ecosystem like Theano and TensorFlow. Tap into their power in a few lines of code using Keras, the best-of-breed applied deep learning library. In this mega Ebook is written in the friendly...
Machine Learning Mastery Pty. Ltd. — 255 p. Deep learning is the most interesting and powerful machine learning technique right now. Top deep learning libraries are available on the Python ecosystem like Theano and TensorFlow. Tap into their power in a few lines of code using Keras, the best-of-breed applied deep learning library. In this mega Ebook is written in the friendly...
Machine Learning Mastery, 2017. — 246 p. Welcome to Long Short-Term Memory Networks With Python. Long Short-Term Memory (LSTM) recurrent neural networks are one of the most interesting types of deep learning at the moment. They have been used to demonstrate world-class results in complex problem domains such as language translation, automatic image captioning, and text...
With contributions by Nicholas Locascio. — New York: O’Reilly Media, 2017. — 298 p. — ISBN: 978-1-491-92561-4. With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research that is paving the way for modern machine learning. This book uses exposition and examples to help you understand major concepts in this complicated...
With contributions by Nicholas Locascio. — New York: O’Reilly Media, 2017. — 298 p. — ISBN: 978-1-491-92561-4. With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research that is paving the way for modern machine learning. This book uses exposition and examples to help you understand major concepts in this complicated...
2nd Edition. — O’Reilly Media, 2022. — 387 p. — ISBN: 978-1-492-08218-7. We're in the midst of an AI research explosion. Deep learning has unlocked superhuman perception that has powered our push toward self-driving vehicles, the ability to defeat human experts at a variety of difficult games including Go and Starcraft, and even generate essays with shockingly coherent prose....
2nd Edition. — O’Reilly Media, 2022. — 387 p. — ISBN: 978-1-492-08218-7. We're in the midst of an AI research explosion. Deep learning has unlocked superhuman perception that has powered our push toward self-driving vehicles, the ability to defeat human experts at a variety of difficult games including Go and Starcraft, and even generate essays with shockingly coherent prose....
2nd Edition. — O’Reilly Media, 2022. — 387 p. — ISBN: 978-1-492-08218-7. We're in the midst of an AI research explosion. Deep learning has unlocked superhuman perception that has powered our push toward self-driving vehicles, the ability to defeat human experts at a variety of difficult games including Go and Starcraft, and even generate essays with shockingly coherent prose....
2nd Edition. — O’Reilly Media, 2022. — 390 p. — ISBN: 978-1-492-08218-7. We're in the midst of an AI research explosion. Deep learning has unlocked superhuman perception that has powered our push toward self-driving vehicles, the ability to defeat human experts at a variety of difficult games including Go and Starcraft, and even generate essays with shockingly coherent prose....
Amazon Kindle Publishing, 2019. — 170 р. — ISBN: 1092562222. Build your Own Neural Network through easy-to-follow instruction and examples. Thanks this easy tutorial you’ll learn the fundamentals of Deep learning and build your very own Neural Network in Python using TensorFlow, Keras, PyTorch, and Theano. While you have the option of spending thousands of dollars on a big and...
Amazon Kindle Publishing, 2019. — 170 р. — ISBN: 1092562222. Build your Own Neural Network through easy-to-follow instruction and examples. Thanks this easy tutorial you’ll learn the fundamentals of Deep learning and build your very own Neural Network in Python using TensorFlow, Keras, PyTorch, and Theano. While you have the option of spending thousands of dollars on a big and...
Manning Publications, 2020. — 632 p. — ISBN: 978-1-617296-17-8. Deep learning has transformed the fields of computer vision, image processing, and natural language applications. Thanks to TensorFlow.js, now JavaScript developers can build deep learning apps without relying on Python or R. Deep Learning with JavaScript shows developers how they can bring DL technology to the...
Manning Publications, 2020. — 560 p. — ISBN: 978-1-617296-17-8. Code files only! Deep learning has transformed the fields of computer vision, image processing, and natural language applications. Thanks to TensorFlow.js, now JavaScript developers can build deep learning apps without relying on Python or R. Deep Learning with JavaScript shows developers how they can bring DL...
IOP Publishing, 2024. — 365 p. — ISBN 978-0-7503-6242-9. This book, together with the accompanying Python codes, provides a thorough and extensive guide for mastering advanced computer vision techniques for image processing by using the open-source machine learning framework PyTorch. Known for its user-friendly interface and Python programming style, PyTorch is accessible and...
IOP Publishing, 2024. — 365 p. — ISBN 978-0-7503-6242-9. This book, together with the accompanying Python codes, provides a thorough and extensive guide for mastering advanced computer vision techniques for image processing by using the open-source machine learning framework PyTorch. Known for its user-friendly interface and Python programming style, PyTorch is accessible and...
Springer, 2020. — 768 p. — (Springer Series in the Data Sciences). — ISBN: 9783030367206, 9783030367213. This book describes how neural networks operate from the mathematical perspective, having in mind that the success of the neural networks methods should not be determined by trial-and-error or luck, but by a clear mathematical analysis. The main goal of the present work is...
Wiley, 2021. — 435 p. — ISBN 9781119646143. Deep Learning for the Earth Sciences: Explore this insightful treatment of deep learning in the field of earth sciences, from four leading voices Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link...
Wiley, 2021. — 435 p. — ISBN 9781119646143. Deep Learning for the Earth Sciences: Explore this insightful treatment of deep learning in the field of earth sciences, from four leading voices Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link...
Wiley-Scrivener, 2023. — 472 p. — (Artificial Intelligence and Soft Computing for Industrial Transformation). In-depth analysis of Deep Learning-based cyber-IoT systems and security which will be the industry leader for the next ten years. Deep Learning (also known as deep structured learning) is part of a broader family of Machine Learning methods based on artificial neural...
Anupam Ghosh, Jyotsna Kumar Mandal, Rajdeep Chakraborty, S. Balamurugan. — Wiley-Scrivener, 2023. — 480 p. — (Artificial Intelligence and Soft Computing for Industrial Transformation). — ISBN-13: 978-1119857211. In-depth analysis of Deep Learning-based cyber-IoT systems and security which will be the industry leader for the next ten years. Deep Learning (also known as deep...
Anupam Ghosh, Jyotsna Kumar Mandal, Rajdeep Chakraborty, S. Balamurugan. — Wiley-Scrivener, 2023. — 480 p. — (Artificial Intelligence and Soft Computing for Industrial Transformation). — ISBN-13: 978-1119857211. In-depth analysis of Deep Learning-based cyber-IoT systems and security which will be the industry leader for the next ten years. Deep Learning (also known as deep...
Anupam Ghosh, Jyotsna Kumar Mandal, Rajdeep Chakraborty, S. Balamurugan. — Wiley-Scrivener, 2023. — 480 p. — (Artificial Intelligence and Soft Computing for Industrial Transformation). — ISBN-13: 978-1119857211. In-depth analysis of Deep Learning-based cyber-IoT systems and security which will be the industry leader for the next ten years. Deep Learning (also known as deep...
Academic Press, 2021. — 230 p. — ISBN 978-0-323-90184-0. Deep Learning for Chest Radiographs enumerates different strategies implemented by the authors for designing an efficient convolution neural network-based computer-aided classification (CAC) system for binary classification of chest radiographs into "Normal" and "Pneumonia." Pneumonia is an infectious disease mostly...
Academic Press, 2021. — 230 p. — ISBN 978-0-323-90184-0. Deep Learning for Chest Radiographs enumerates different strategies implemented by the authors for designing an efficient convolution neural network-based computer-aided classification (CAC) system for binary classification of chest radiographs into "Normal" and "Pneumonia." Pneumonia is an infectious disease mostly...
The MIT Press, 2019. — 187 p. — ISBN: 9780262039512. A project-based guide to the basics of deep learning. This concise, project-driven guide to deep learning takes readers through a series of program-writing tasks that introduce them to the use of deep learning in such areas of artificial intelligence as computer vision, natural-language processing, and reinforcement learning....
CRC Press, 2022. — 177 р. — (Explainable AI (XAI) for Engineering Applications)/ Over the last decade, progress in deep learning has had a profound and transformational effect on many complex problems, including speech recognition, machine translation, natural language understanding, and computer vision. As a result, computers can now achieve human-competitive performance in a...
Springer, 2019. — 109 p. This book presents the latest research on hierarchical deep learning for multi-modal sentiment analysis. Further, it analyses sentiments in Twitter blogs from both textual and visual content using hierarchical deep learning networks: hierarchical gated feedback recurrent neural networks (HGFRNNs). Several studies on deep learning have been conducted to...
Springer, 2017. — 109 p. This book proposes complex hierarchical deep architectures (HDA) for predicting bankruptcy, a topical issue for business and corporate institutions that in the past has been tackled using statistical, market-based and machine-intelligence prediction models. The HDA are formed through fuzzy rough tensor deep staking networks (FRTDSN) with structured,...
Manning Publications, 2024. — 550 p. — ISBN 1617296481. Shine a spotlight into the deep learning “black box”. This comprehensive and detailed guide reveals the mathematical and architectural concepts behind deep learning models, so you can customize, maintain, and explain them more effectively. Inside Math and Architectures of Deep Learning you will find: Math, theory, and...
Manning Publications, 2024. — 552 p. — ISBN 978-1617296482. Shine a spotlight into the deep learning “black box”. This comprehensive and detailed guide reveals the mathematical and architectural concepts behind deep learning models, so you can customize, maintain, and explain them more effectively. Inside Math and Architectures of Deep Learning you will find: Math, theory, and...
Manning Publications, 2024. — 552 p. — ISBN 978-1617296482. Shine a spotlight into the deep learning “black box”. This comprehensive and detailed guide reveals the mathematical and architectural concepts behind deep learning models, so you can customize, maintain, and explain them more effectively. Inside Math and Architectures of Deep Learning you will find: Math, theory, and...
Manning Publications, 2024. — 552 p. — ISBN 978-1617296482. Shine a spotlight into the deep learning “black box”. This comprehensive and detailed guide reveals the mathematical and architectural concepts behind deep learning models, so you can customize, maintain, and explain them more effectively. Inside Math and Architectures of Deep Learning you will find: Math, theory, and...
Springer, 2021. — 403 p. — ISBN 978-981-16-2232-8. This book systematically introduces readers to the theory of deep learning and explores its practical applications based on the MindSpore AI computing framework. Divided into 14 chapters, the book covers deep learning, deep neural networks (DNNs), convolutional neural networks (CNNs), recurrent neural networks (RNNs),...
Springer, 2021. — 403 p. — ISBN 978-981-16-2232-8. This book systematically introduces readers to the theory of deep learning and explores its practical applications based on the MindSpore AI computing framework. Divided into 14 chapters, the book covers deep learning, deep neural networks (DNNs), convolutional neural networks (CNNs), recurrent neural networks (RNNs),...
World Scientific Publishing Co. Pte. Ltd., 2021. — 327 p. — ISBN 9811218838. Deep Learning has achieved great success in many challenging research areas, such as image recognition and natural language processing. The key merit of deep learning is to automatically learn good feature representation from massive data conceptually. In this book, we will show that the deep learning...
World Scientific Publishing Co. Pte. Ltd., 2021. — 327 p. — ISBN 9811218838. Deep Learning has achieved great success in many challenging research areas, such as image recognition and natural language processing. The key merit of deep learning is to automatically learn good feature representation from massive data conceptually. In this book, we will show that the deep learning...
World Scientific Publishing Co. Pte. Ltd., 2021. — 324 p. — ISBN 13: 9789811218835. Deep Learning has achieved great success in many challenging research areas, such as image recognition and natural language processing. The key merit of deep learning is to automatically learn good feature representation from massive data conceptually. In this book, we will show that the deep...
World Scientific Publishing Co. Pte. Ltd., 2021. — 324 p. — ISBN-13: 9789811218835. Deep Learning has achieved great success in many challenging research areas, such as image recognition and natural language processing. The key merit of deep learning is to automatically learn good feature representation from massive data conceptually. In this book, we will show that the deep...
Nova, 2020. - 338p. - ISBN: 9789813348844 From the successful application of deep learning (DL) in AlphaGo in 2012 to the recent advances in edge computing, artificial intelligence (AI) has continued to develop over the years. In the face of the current sweeping trend of AI, ensemble learning (EL) is expected to be further applied to DL and AI for developing higher-level...
Springer, 2023. — 314 p. A critical challenge in Deep Learning is the vulnerability of Deep Learning networks to security attacks from intelligent cyber adversaries. Even innocuous perturbations to the training data can be used to manipulate the behaviour of deep networks in unintended ways. In this book, we review the latest developments in adversarial attack technologies in...
Chivukula Aneesh Sreevallabh, Yang Xinghao, Liu Bo, Liu Wei, Zhou Wanlei. — Springer, 2023. — 319 p. — ISBN 978-3-030-99772-4. A critical challenge in Deep Learning is the vulnerability of Deep Learning networks to security attacks from intelligent cyber adversaries. Even innocuous perturbations to the training data can be used to manipulate the behaviour of deep networks in...
Chivukula Aneesh Sreevallabh, Yang Xinghao, Liu Bo, Liu Wei, Zhou Wanlei. — Springer, 2023. — 319 p. — ISBN 978-3-030-99772-4. A critical challenge in Deep Learning is the vulnerability of Deep Learning networks to security attacks from intelligent cyber adversaries. Even innocuous perturbations to the training data can be used to manipulate the behaviour of deep networks in...
Chivukula Aneesh Sreevallabh, Yang Xinghao, Liu Bo, Liu Wei, Zhou Wanlei. — Springer, 2023. — 319 p. — ISBN 978-3-030-99772-4. A critical challenge in Deep Learning is the vulnerability of Deep Learning networks to security attacks from intelligent cyber adversaries. Even innocuous perturbations to the training data can be used to manipulate the behaviour of deep networks in...
2nd Edition. — Manning, 2020. — 214 p. — (MEAP Version 4). — ISBN: 9781617294433. Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. You’ll learn directly from the creator of Keras, Fran?ois Chollet, building your understanding through intuitive explanations and practical examples. Updated from the original...
Manning, 2018. — 386 p. — ISBN: 9781617294433. This book introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications...
2nd Edition. — Manning Publications, 2021. — 504 p. — ISBN: 978-1617296864. Unlock the groundbreaking advances of deep learning with this extensively revised new edition of the bestselling original. Learn directly from the creator of Keras and master practical Python deep learning techniques that are easy to apply in the real world. In Deep Learning with Python, Second Edition...
2nd Edition. — Manning Publications, 2021. — 504 p. — ISBN: 978-1617296864. Unlock the groundbreaking advances of deep learning with this extensively revised new edition of the bestselling original. Learn directly from the creator of Keras and master practical Python deep learning techniques that are easy to apply in the real world. In Deep Learning with Python, Second Edition...
2nd Edition. — Manning Publications, 2021. — 504 p. — ISBN: 978-1617296864. Unlock the groundbreaking advances of deep learning with this extensively revised new edition of the bestselling original. Learn directly from the creator of Keras and master practical Python deep learning techniques that are easy to apply in the real world. In Deep Learning with Python, Second Edition...
2nd Edition. — Manning Publications, 2021. — 504 p. — ISBN: 978-1617296864. Unlock the groundbreaking advances of deep learning with this extensively revised new edition of the bestselling original. Learn directly from the creator of Keras and master practical Python deep learning techniques that are easy to apply in the real world. In Deep Learning with Python, Second Edition...
Manning, 2018. — 325 p. Artificial intelligence has made some incredible leaps. Deep learning systems now deliver near-human speech and image recognition, not to mention machines capable of beating world champion Go masters. Deep learning applies to a widening range of problems, such as question answering, machine translation, and optical character recognition. It's behind photo...
Manning, 2018. — 325 p. Artificial intelligence has made some incredible leaps. Deep learning systems now deliver near-human speech and image recognition, not to mention machines capable of beating world champion Go masters. Deep learning applies to a widening range of problems, such as question answering, machine translation, and optical character recognition. It's behind photo...
Manning, 2018. — 325 p. Artificial intelligence has made some incredible leaps. Deep learning systems now deliver near-human speech and image recognition, not to mention machines capable of beating world champion Go masters. Deep learning applies to a widening range of problems, such as question answering, machine translation, and optical character recognition. It's behind photo...
Manning, 2018. — 325 p. Artificial intelligence has made some incredible leaps. Deep learning systems now deliver near-human speech and image recognition, not to mention machines capable of beating world champion Go masters. Deep learning applies to a widening range of problems, such as question answering, machine translation, and optical character recognition. It's behind...
Manning Publications, 2018. — 392 p. — ISBN13: 978-1617295546. Deep Learning with R introduces the world of deep learning using the powerful Keras library and its R language interface. The book builds your understanding of deep learning through intuitive explanations and practical examples. Machine learning has made remarkable progress in recent years. Deep-learning systems now...
Manning Publications, 2018. — 392 p. — ISBN13: 978-1617295546. Deep Learning with R introduces the world of deep learning using the powerful Keras library and its R language interface. The book builds your understanding of deep learning through intuitive explanations and practical examples. Machine learning has made remarkable progress in recent years. Deep-learning systems now...
Manning Publications, 2018. — 392 p. — ISBN13: 978-1617295546. Deep Learning with R introduces the world of deep learning using the powerful Keras library and its R language interface. The book builds your understanding of deep learning through intuitive explanations and practical examples. Machine learning has made remarkable progress in recent years. Deep-learning systems now...
Manning Publications, 2017. — 384 p. — ISBN13: 9781617294433. Целевая аудитория: опытные разработчики. В данной книге изучаются методы глубокого обучения с использованием популярной в настоящее время библиотеки Keras. Книга написана создателем этой библиотеки и содержит многочисленные практические примеры по её применению. Также вместе с автором вы изучите концепции создания...
Manning Publications, 2017. — 384 p. — ISBN13: 9781617294433. Целевая аудитория: опытные разработчики. В данной книге изучаются методы глубокого обучения с использованием популярной в настоящее время библиотеки Keras. Книга написана создателем этой библиотеки и содержит многочисленные практические примеры по её применению. Также вместе с автором вы изучите концепции создания...
Manning Publications, 2017. — 384 p. Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher Fran?ois Chollet, this book builds your understanding through intuitive explanations and practical examples. About the Technology Machine learning has made remarkable...
New Delhi: BPB Publications, 2019. — 357 p. Deep Learning with Kelp.Net is the ultimate reference for C# .Net developers who are passionate about deep learning. Readers will learn all the skills necessary to develop powerful, scalable and flexible deep learning models from a fluid and easy to use API. Upon completing the book the reader will have all the tools necessary to add...
BPB Publications, 2019. — 357 p. — ISBN 978-93-88511-018. Get hands on with Kelp.Net, Microsoft’s latest Deep Learning framework Key Features Deep Learning Basics The ultimate Kelp.Net reference guide Develop state of the art deep learning applications C# deep learning code Develop advanced deep learning models with minimal code Develop your own advanced deep learning models...
LazyProgrammer, 2016. — 59 p. This is the 3rd part in my Data Science and Machine Learning series on Deep Learning in Python. At this point, you already know a lot about neural networks and deep learning, including not just the basics like backpropagation, but how to improve it using modern techniques like momentum and adaptive learning rates. You've already written deep neural...
LazyProgrammer, 2016. — 59 p. This is the 3rd part in my Data Science and Machine Learning series on Deep Learning in Python. At this point, you already know a lot about neural networks and deep learning, including not just the basics like backpropagation, but how to improve it using modern techniques like momentum and adaptive learning rates. You've already written deep neural...
LazyProgrammer, 2016. — 59 p. This is the 3rd part in my Data Science and Machine Learning series on Deep Learning in Python. At this point, you already know a lot about neural networks and deep learning, including not just the basics like backpropagation, but how to improve it using modern techniques like momentum and adaptive learning rates. You've already written deep neural...
LazyProgrammer, 2016. — 59 p. This is the 3rd part in my Data Science and Machine Learning series on Deep Learning in Python. At this point, you already know a lot about neural networks and deep learning, including not just the basics like backpropagation, but how to improve it using modern techniques like momentum and adaptive learning rates. You've already written deep neural...
Quantum Technologies, 2023. — 276 p. Dive into the world of Generative Deep Learning with Python, mastering GANs, VAEs, & autoregressive models through projects & advanced topics. Gain practical skills & theoretical knowledge to create groundbreaking AI applications. Key Features: Comprehensive coverage of deep learning and generative models. In-depth exploration of GANs, VAEs,...
The Institution of Engineering and Technology, 2020. — 329 p. — ISBN 978-1-78561-769-0. This book presents and discusses innovative ideas in the design, modelling, implementation, and optimization of hardware platforms for neural networks. The rapid growth of server, desktop, and embedded applications based on deep learning has brought about a renaissance in interest in neural...
The Institution of Engineering and Technology, 2020. — 328 p. — ISBN: 978-1-78561-769-0. This book presents and discusses innovative ideas in the design, modelling, implementation, and optimization of hardware platforms for neural networks. The rapid growth of server, desktop, and embedded applications based on deep learning has brought about a renaissance in interest in neural...
Amazon Digital Services LLC, 2018. — 98 p. — ASIN: B07K2Q6DXH. Deep learning is a process that widens the range of most artificial intelligence problems like speech recognition, image classification, question answering, optical character recognition, and transforming text to speech. It is true that deep learning is a complex subject to learn and understand, but it is not...
Amazon Digital Services LLC, 2018. — 98 p. — ASIN: B07K2Q6DXH. Deep learning is a process that widens the range of most artificial intelligence problems like speech recognition, image classification, question answering, optical character recognition, and transforming text to speech. It is true that deep learning is a complex subject to learn and understand, but it is not...
Amazon Digital Services LLC, 2018. — 108 р. Deep learning is a process that widens the range of most artificial intelligence problems like speech recognition, image classification, question answering, optical character recognition, and transforming text to speech. It is true that deep learning is a complex subject to learn and understand, but it is not difficult for most...
Amazon Digital Services LLC, 2018. — 108 р. Deep learning is a process that widens the range of most artificial intelligence problems like speech recognition, image classification, question answering, optical character recognition, and transforming text to speech. It is true that deep learning is a complex subject to learn and understand, but it is not difficult for most...
Amazon Digital Services LLC, 2018. — 108 р. Deep learning is a process that widens the range of most artificial intelligence problems like speech recognition, image classification, question answering, optical character recognition, and transforming text to speech. It is true that deep learning is a complex subject to learn and understand, but it is not difficult for most...
Packt, 2020. — 364 p. — ASIN B085P1JG2W. A comprehensive guide to getting well-versed with the mathematical techniques for building modern deep learning architectures Key Features Understand linear algebra, calculus, gradient algorithms, and other concepts essential for training deep neural networks Learn the mathematical concepts needed to understand how deep learning models...
Packt, 2020. — 364 p. — ASIN B085P1JG2W. A comprehensive guide to getting well-versed with the mathematical techniques for building modern deep learning architectures Key Features Understand linear algebra, calculus, gradient algorithms, and other concepts essential for training deep neural networks Learn the mathematical concepts needed to understand how deep learning models...
Packt, 2020. — 364 p. — ASIN B085P1JG2W A comprehensive guide to getting well-versed with the mathematical techniques for building modern deep learning architectures Key Features Understand linear algebra, calculus, gradient algorithms, and other concepts essential for training deep neural networks Learn the mathematical concepts needed to understand how deep learning models...
Packt, 2020. — 364 p. — ASIN B085P1JG2W. A comprehensive guide to getting well-versed with the mathematical techniques for building modern deep learning architectures Key Features Understand linear algebra, calculus, gradient algorithms, and other concepts essential for training deep neural networks Learn the mathematical concepts needed to understand how deep learning models...
LazyProgrammer, 2016. — 71 p. Deep learning is making waves. At the time of this writing (March 2016), Google’s AlghaGo program just beat 9-dan professional Go player Lee Sedol at the game of Go, a Chinese board game. Experts in the field of Artificial Intelligence thought we were 10 years away from achieving a victory against a top professional Go player, but progress seems to...
LazyProgrammer, 2016. — 71 p. Deep learning is making waves. At the time of this writing (March 2016), Google’s AlghaGo program just beat 9-dan professional Go player Lee Sedol at the game of Go, a Chinese board game. Experts in the field of Artificial Intelligence thought we were 10 years away from achieving a victory against a top professional Go player, but progress seems to...
LazyProgrammer, 2016. — 71 p. Deep learning is making waves. At the time of this writing (March 2016), Google’s AlghaGo program just beat 9-dan professional Go player Lee Sedol at the game of Go, a Chinese board game. Experts in the field of Artificial Intelligence thought we were 10 years away from achieving a victory against a top professional Go player, but progress seems to...
LazyProgrammer, 2016. — 71 p. Deep learning is making waves. At the time of this writing (March 2016), Google’s AlghaGo program just beat 9-dan professional Go player Lee Sedol at the game of Go, a Chinese board game. Experts in the field of Artificial Intelligence thought we were 10 years away from achieving a victory against a top professional Go player, but progress seems to...
NOWPress, 2013. — 198 p. This monograph provides an overview of general deep learning methodology and its applications to a variety of signal and information processing tasks. The application areas are chosen with the following three criteria in mind: (1) expertise or knowledge of the authors; (2) the application areas that have already been transformed by the successful use of...
Springer, 2018. — 338 p. — ISBN: 978-981-10-5208-8. In recent years, deep learning has fundamentally changed the landscapes of a number of areas in artificial intelligence, including speech, vision, natural language, robotics, and game playing. In particular, the striking success of deep learning in a wide variety of natural language processing (NLP) applications has served as...
Springer, 2018. — 338 p. — ISBN: 978-981-10-5208-8. In recent years, deep learning has fundamentally changed the landscapes of a number of areas in artificial intelligence, including speech, vision, natural language, robotics, and game playing. In particular, the striking success of deep learning in a wide variety of natural language processing (NLP) applications has served as...
Packt Publishing, 2022. — 470 p. — ISBN 978-1-80461-544-7. Learn concepts, methodologies, and applications of deep learning for building predictive models from complex genomics data sets to overcome challenges in the life sciences and biotechnology industries Key Features - Apply deep learning algorithms to solve real-world problems in the field of genomics - Extract biological...
Packt, 2018. — 271 p. — ISBN: 1785880365. Deep Learning a trending topic in the field of Artificial Intelligence today and can be considered to be an advanced form of machine learning, which is quite tricky to master. This book will help you take your first steps in training efficient deep learning models and applying them in various practical scenarios. You will model, train,...
Packt, 2018. — 271 p. — ISBN: 1785880365. Deep Learning a trending topic in the field of Artificial Intelligence today and can be considered to be an advanced form of machine learning, which is quite tricky to master. This book will help you take your first steps in training efficient deep learning models and applying them in various practical scenarios. You will model, train,...
Packt Publishing, 2018. — 420 p. — ISBN: 978-1-78588-036-0. Get to grips with the essentials of deep learning by leveraging the power of Python Deep Learning a trending topic in the field of Artificial Intelligence today and can be considered to be an advanced form of machine learning, which is quite tricky to master. This book will help you take your first steps in training...
Packt Publishing, 2018. — 420 p. — ISBN: 978-1-78588-036-0. Get to grips with the essentials of deep learning by leveraging the power of Python Deep Learning a trending topic in the field of Artificial Intelligence today and can be considered to be an advanced form of machine learning, which is quite tricky to master. This book will help you take your first steps in training...
Cambridge: Cambridge University Press, 2022. - 361 p. - ISBN 1108835082. The Science of Deep Learning emerged from courses taught by the author that have provided thousands of students with training and experience for their academic studies. prepared them for careers in deep learning, machine learning. artificial intelligence in top companies in industry and academia. The book...
Springer, 2025. — 213 p. — ISBN 978-981-97-9333-4. Анализ позы человека: глубокое обучение соответствует кинематике человека в видео. With the rapid technological advancements and the proliferation of digital media in the contemporary world, the study of human behavior using computer technologies has taken on new dimensions. Among the most intriguing and consequential areas of...
PB Publications, 2023. — 237 p. — ISBN 978-93-5551-105-8. A step-by-step guide to get started with Machine Learning. Key Features - Understand different types of Machine Learning like Supervised, Unsupervised, Semi-supervised, and Reinforcement learning. - Learn how to implement Machine Learning algorithms effectively and efficiently. - Get familiar with the various libraries &...
PB Publications, 2023. — 237 p. — ISBN 978-93-5551-105-8. A step-by-step guide to get started with Machine Learning. Key Features - Understand different types of Machine Learning like Supervised, Unsupervised, Semi-supervised, and Reinforcement learning. - Learn how to implement Machine Learning algorithms effectively and efficiently. - Get familiar with the various libraries &...
PB Publications, 2023. — 237 p. — ISBN 978-93-5551-105-8. A step-by-step guide to get started with Machine Learning. Key Features - Understand different types of Machine Learning like Supervised, Unsupervised, Semi-supervised, and Reinforcement learning. - Learn how to implement Machine Learning algorithms effectively and efficiently. - Get familiar with the various libraries &...
PB Publications, 2023. — 237 p. — ISBN 978-93-5551-105-8. A step-by-step guide to get started with Machine Learning. Key Features - Understand different types of Machine Learning like Supervised, Unsupervised, Semi-supervised, and Reinforcement learning. - Learn how to implement Machine Learning algorithms effectively and efficiently. - Get familiar with the various libraries &...
Springer, 2025. — 222 p. This book takes a balanced approach between theoretical understanding and real time applications. All topics show how to explore, build, evaluate and optimize Deep Learning models with Computer Vision. Deep Learning is integrated with Computer Vision to enhance the performance of image classification with localization, object detection, object...
Manning, 2020. — 297 p. — ISBN: 9781617296079. Probabilistic Deep Learning with Python shows how probabilistic deep learning models gives readers the tools to identify and account for uncertainty and potential errors in their results. Starting by applying the underlying maximum likelihood principle of curve fitting to deep learning, readers will move on to using the...
Manning, 2020. — 297 p. — ISBN: 9781617296079. Probabilistic Deep Learning with Python shows how probabilistic deep learning models gives readers the tools to identify and account for uncertainty and potential errors in their results. Starting by applying the underlying maximum likelihood principle of curve fitting to deep learning, readers will move on to using the...
Manning Publications Co., 2020. — 297 p. — ISBN: 9781617296079. Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability teaches the increasingly popular probabilistic approach to deep learning that allows you to refine your results more quickly and accurately without much trial-and-error testing. Emphasizing practical techniques that use the Python-based...
Manning Publications Co., 2020. — 297 p. — ISBN: 9781617296079. Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability teaches the increasingly popular probabilistic approach to deep learning that allows you to refine your results more quickly and accurately without much trial-and-error testing. Emphasizing practical techniques that use the Python-based...
Manning Publications, 2020. — 300 p. — ISBN: 978-1617296079. About the Technology Probabilistic deep learning models are better suited to dealing with the noise and uncertainty of real world data — a crucial factor for self-driving cars, scientific results, financial industries, and other accuracy-critical applications. By utilizing probabilistic techniques, deep learning...
Manning Publications, 2020. — 300 p. — ISBN: 978-1617296079. About the Technology Probabilistic deep learning models are better suited to dealing with the noise and uncertainty of real world data — a crucial factor for self-driving cars, scientific results, financial industries, and other accuracy-critical applications. By utilizing probabilistic techniques, deep learning...
Manning Publications, 2020. — 300 p. — ISBN: 978-1617296079. About the Technology Probabilistic deep learning models are better suited to dealing with the noise and uncertainty of real world data — a crucial factor for self-driving cars, scientific results, financial industries, and other accuracy-critical applications. By utilizing probabilistic techniques, deep learning...
Manning Publications, 2020. — 300 p. — ISBN: 978-1617296079. About the Technology Probabilistic deep learning models are better suited to dealing with the noise and uncertainty of real world data — a crucial factor for self-driving cars, scientific results, financial industries, and other accuracy-critical applications. By utilizing probabilistic techniques, deep learning...
Manning Publications, 2020. — 300 p. — ISBN: 978-1617296079. Code files only! About the Technology Probabilistic deep learning models are better suited to dealing with the noise and uncertainty of real world data — a crucial factor for self-driving cars, scientific results, financial industries, and other accuracy-critical applications. By utilizing probabilistic techniques,...
Manning Publications Co., 2020. — 297 p. — ISBN: 9781617296079. Code files only! Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability teaches the increasingly popular probabilistic approach to deep learning that allows you to refine your results more quickly and accurately without much trial-and-error testing. Emphasizing practical techniques that use the...
Amazon Digital Services LLC, 2020. — 148 р. — ASIN B083S1DDB7. Learn to create inventive programs on your Machine Learning&Deep Learning and Python―with no programming experience required. Discover how to configure, write Python scripts, create user-friendly GUIs.Projects include a object detection by find object with camera, tracking motion. Hands-on Deep Learning&Machine...
Addison-Wesley, 2021. — 800 p. — ISBN 9780137470198. NVIDIA's Full-Color Guide to Deep Learning with TensorFlow: All You Need to Get Started and Get Results Deep learning is a key component of today's exciting advances in machine learning and artificial intelligence. Learning Deep Learning is a complete guide to deep learning with TensorFlow, the #1 Python library for building...
Pearson Education, 2022. — 747 p. — ISBN 978-0-13-747035-8. NVIDIA's Full-Color Guide to Deep Learning: All You Need to Get Started and Get Results "To enable everyone to be part of this historic revolution requires the democratization of AI knowledge and resources. This book is timely and relevant towards accomplishing these lofty goals." -- From the foreword by Dr. Anima...
Addison-Wesley Professional, 2021. — 752 p. — ISBN 978-0137470358. NVIDIA's Full-Color Guide to Deep Learning: All You Need to Get Started and Get Results "To enable everyone to be part of this historic revolution requires the democratization of AI knowledge and resources. This book is timely and relevant towards accomplishing these lofty goals." -- From the foreword by Dr....
Manning, 2021. — 480 p. — ISBN: 9781617296192. The definitive M&E price book with additions to the measured works, updates to approximate estimating and new engineering features. Spon's Mechanical and Electrical Services Price Book 2021 continues to be the most comprehensive and best annual services engineering price book currently available, providing detailed pricing...
Manning, 2019. — 396 p. The book teaches you to apply deep learning techniques to solve real-world computer vision problems. In his straightforward and accessible style, DL and CV expert Mohamed Elgendy introduces you to the concept of visual intuition—how a machine learns to understand what it sees. Then you’ll explore the DL algorithms used in different CV applications. You’ll...
Manning, 2021. — 480 p. — ISBN: 9781617296192. The definitive M&E price book with additions to the measured works, updates to approximate estimating and new engineering features. Spon's Mechanical and Electrical Services Price Book 2021 continues to be the most comprehensive and best annual services engineering price book currently available, providing detailed pricing...
Manning Publications Co., 2021. — 475 p. — ISBN: 978-1617296192. Computer vision is central to many leading-edge innovations, including self-driving cars, drones, augmented reality, facial recognition, and much, much more. Amazing new computer vision applications are developed every day, thanks to rapid advances in AI and deep learning (DL). Deep Learning for Vision Systems...
Manning Publications Co., 2021. — 475 p. — ISBN: 978-1617296192. Computer vision is central to many leading-edge innovations, including self-driving cars, drones, augmented reality, facial recognition, and much, much more. Amazing new computer vision applications are developed every day, thanks to rapid advances in AI and deep learning (DL). Deep Learning for Vision Systems...
Manning Publications Co., 2021. — 475 p. — ISBN: 978-1617296192. Code files only! Computer vision is central to many leading-edge innovations, including self-driving cars, drones, augmented reality, facial recognition, and much, much more. Amazing new computer vision applications are developed every day, thanks to rapid advances in AI and deep learning (DL). Deep Learning for...
Birmingham: Packt Publishing, 2023. - 349 p. - ISBN 180324013X. Achieve TensorFlow certification with this comprehensive guide covering all exam topics using a hands-on, step-by-step approach—perfect for aspiring TensorFlow developers. Key Features Build real-world computer vision, natural language, and time series applications. Learn how to overcome issues such as overfitting...
Wiley-IEEE Press, 2023. — 274 p. — (IEEE Press Series on Control Systems Theory and Applications). — ISBN 9781119808572. Model-Based Reinforcement Learning Explore a comprehensive and practical approach to reinforcement learning. Reinforcement learning is an essential paradigm of machine learning, wherein an intelligent agent performs actions that ensure optimal behavior from...
Springer, 2025. — 298 p. Deep Learning has significantly reshaped a variety of technologies, such as image processing, natural language processing (NLP), and audio processing. The excellent generalizability of Deep Learning is like a “cloud” to conventional complexity-based learning theory: the over-parameterization of Deep Learning makes almost all existing tools vacuous. This...
Springer, 2022. — 354 p. — (Computational Intelligence Methods and Applications). — ISBN 3031044193. Applied Deep Learning: Tools, Techniques, and Implementation , is aimed at students, academics and industry practitioners to provide them with a conceptual overview of the field. Students can use this book to supplement undergraduate, postgraduate and doctoral studies. Academics...
Springer Cham, 2022. — 341 p. — (Computational Intelligence Methods and Applications). — ISBN 978-3-031-04420-5. This book focuses on the applied aspects of artificial intelligence using enterprise frameworks and technologies. The book is applied in nature and will equip the reader with the necessary skills and understanding for delivering enterprise ML technologies. It will be...
Manning Publications Co, 2021. — 471 p. — ISBN 9781617298264. Discover best practices, reproducible architectures, and design patterns to help guide deep learning models from the lab into production. In Deep Learning Patterns and Practices you will learn: Internal functioning of modern convolutional neural networks Procedural reuse design pattern for CNN architectures Models...
Manning Publications Co, 2021. — 471 p. — ISBN 9781617298264. Discover best practices, reproducible architectures, and design patterns to help guide deep learning models from the lab into production. In Deep Learning Patterns and Practices you will learn: Internal functioning of modern convolutional neural networks Procedural reuse design pattern for CNN architectures Models...
Manning Publications Co, 2021. — 471 p. — ISBN 9781617298264. Discover best practices, reproducible architectures, and design patterns to help guide deep learning models from the lab into production. In Deep Learning Patterns and Practices you will learn: Internal functioning of modern convolutional neural networks Procedural reuse design pattern for CNN architectures Models...
Boca Raton: CRC Press, 2023. — 228 p. The leveraging of Artificial Intelligence (AI) for model discovery in dynamical systems is cross-fertilizing and revolutionizing both disciplines, heralding a new era of data-driven science. This book is placed at the forefront of this endeavor, taking model discovery to the next level. Dealing with Artificial Intelligence, this book...
CRC Press, 2023. — 228 р. — (Artificial Intelligence and Robotics Series). — ISBN: 978-1-032-36632-6. The leveraging of Artificial Intelligence (AI) for model discovery in dynamical systems is cross-fertilizing and revolutionizing both disciplines, heralding a new era of data-driven science. This book is placed at the forefront of this endeavor, taking model discovery to the...
Packt Publishing, 2019. — 126 p. — ISBN: 9781838551605. Use the serverless computing approach to save time and money Key Features Save your time by deploying deep learning models with ease using the AWS serverless infrastructure Get a solid grip on AWS services and use them with TensorFlow for efficient deep learning Includes tips, tricks and best practices on serverless deep...
Packt Publishing, 2019. — 126 p. — ISBN: 9781838551605. Use the serverless computing approach to save time and money Key Features Save your time by deploying deep learning models with ease using the AWS serverless infrastructure Get a solid grip on AWS services and use them with TensorFlow for efficient deep learning Includes tips, tricks and best practices on serverless deep...
USA: Applied Data Science Partners Ltd, 2019. — 330 p. — ISBN: 978-1-492-04194-8. Generative modeling is one of the hottest topics in AI. It's now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most...
O’Reilly Media, 2019. — 55 р. — ISBN: 1492041947. Generative modeling is one of the hottest topics in artificial intelligence (AI). Recent advances in the field have shown how it’s possible to teach a machine to excel at human endeavors—such as drawing, composing music, and completing tasks—by generating an understanding of how its actions affect its environment. With this...
Applied Data Science Partners Ltd, 2019. — 330 p. — ISBN: 978-1-492-04194-8. Generative modeling is one of the hottest topics in AI. It’s now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive...
Applied Data Science Partners Ltd, 2019. — 308 p. — ISBN: 978-1-492-04194-8. Generative modeling is one of the hottest topics in AI. It’s now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive...
Applied Data Science Partners Ltd, 2019. — 308 p. — ISBN: 978-1-492-04194-8. Generative modeling is one of the hottest topics in AI. It’s now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive...
2nd Edition. — O’Reilly Media, Inc., 2023. — 453 p. — ISBN: 978-1-098-13418-1. Generative modeling is one of the hottest topics in artificial intelligence. Recent advances in the field have shown how it’s possible to teach a machine to excel at human endeavors–such as drawing, composing music, and completing tasks–by generating an understanding of how its actions affect its...
2nd Edition. — O’Reilly Media, Inc., 2023. — 453 p. — ISBN: 978-1-098-13418-1. Generative modeling is one of the hottest topics in artificial intelligence. Recent advances in the field have shown how it’s possible to teach a machine to excel at human endeavors–such as drawing, composing music, and completing tasks–by generating an understanding of how its actions affect its...
2nd Edition. — O’Reilly Media, Inc., 2023. — 453 p. — ISBN: 978-1-098-13418-1. Generative modeling is one of the hottest topics in artificial intelligence. Recent advances in the field have shown how it’s possible to teach a machine to excel at human endeavors–such as drawing, composing music, and completing tasks–by generating an understanding of how its actions affect its...
The MIT Press, 2023. — 440 р. — ISBN 978-0-262-54637-9. A highly accessible, step-by-step introduction to Deep Learning, written in an engaging, question-and-answer style. The Little Learner introduces Deep Learning from the bottom up, inviting students to learn by doing. With the characteristic humor and Socratic approach of classroom favorites The Little Schemer and The...
The MIT Press, 2023. — 440 р. — ISBN 978-0-262-54637-9. A highly accessible, step-by-step introduction to Deep Learning, written in an engaging, question-and-answer style. The Little Learner introduces Deep Learning from the bottom up, inviting students to learn by doing. With the characteristic humor and Socratic approach of classroom favorites The Little Schemer and The...
The MIT Press, 2023. — 440 р. — ISBN 978-0-262-54637-9. A highly accessible, step-by-step introduction to Deep Learning, written in an engaging, question-and-answer style. The Little Learner introduces Deep Learning from the bottom up, inviting students to learn by doing. With the characteristic humor and Socratic approach of classroom favorites The Little Schemer and The...
Arcler Press, 2022. — 412 p. This book covers different topics from deep learning algorithms, methods and approaches for deep learning, deep learning applications in biology, deep learning applications in medicine, and deep learning applications in pattern recognition systems. Section 1 focuses on methods and approaches for deep learning, describing advancements in deep...
Packt Publishing, 2018. — 334 p. A hands-on guide to deep learning thats filled with intuitive explanations and engaging practical examples Key Features Designed to iteratively develop the skills of Python users who dont have a data science background Covers the key foundational concepts youll need to know when building deep learning systems Full of step-by-step exercises and...
Packt Publishing, 2018. — 334 p. A hands-on guide to deep learning thats filled with intuitive explanations and engaging practical examples Key Features Designed to iteratively develop the skills of Python users who dont have a data science background Covers the key foundational concepts youll need to know when building deep learning systems Full of step-by-step exercises and...
Packt Publishing, 2018. — 334 p. Code files only! A hands-on guide to deep learning thats filled with intuitive explanations and engaging practical examples Key Features Designed to iteratively develop the skills of Python users who dont have a data science background Covers the key foundational concepts youll need to know when building deep learning systems Full of...
Springer Singapore, 2024. — 201 p. — (Transactions on Computer Systems and Networks (TCSN)). — eBook ISBN 978-981-99-9672-8. Offers a special chapter devoted to performance evaluation of deep learning algorithms Demonstrates illustrative colorful block diagrams, figures, and full code examples to clearly present ideas involved Gives contents geared for both professionals and...
Springer Singapore, 2024. — 201 p. — (Transactions on Computer Systems and Networks (TCSN)). — eBook ISBN 978-981-99-9672-8. Offers a special chapter devoted to performance evaluation of deep learning algorithms Demonstrates illustrative colorful block diagrams, figures, and full code examples to clearly present ideas involved Gives contents geared for both professionals and...
Amazon Digital Services LLC, 2018. — 770 р. The last decade and some, has witnessed some remarkable advancements in the area of Deep Learning. This area of Artificial intelligence (AI) has proliferated into many branches - Deep Belief Networks, Recurrent Neural Networks, Convolution Neural Networks, Adversorial Networks, Reinforcement Learning, Capsule Networks and the list...
2nd Edition. — Amazon Digital Services LLC, 2018. — 770 р. The last decade and some, has witnessed some remarkable advancements in the area of Deep Learning. This area of Artificial intelligence (AI) has proliferated into many branches - Deep Belief Networks, Recurrent Neural Networks, Convolution Neural Networks, Adversorial Networks, Reinforcement Learning, Capsule Networks...
CRC Press, 2023. — 208 p. — eBook ISBN: 978-0-429-32125-2. Deep learning is an important element of artificial intelligence, especially in applications such as image classification in which various architectures of neural network, e.g., convolutional neural networks, have yielded reliable results. This book introduces deep learning for time series analysis, particularly for...
CRC Press, 2022. — 219 p. — ISBN 978-0-367-45658-0. Deep Learning in Practice helps you learn how to develop and optimize a model for your projects using Deep Learning (DL) methods and architectures. Key features Demonstrates a quick review on Python, NumPy, and TensorFlow fundamentals. Explains and provides examples of deploying TensorFlow and Keras in several projects....
BPB Publications, 2023. — 477 р. — ISBN: 978-93-5551-194-2. Mathematical Codebook to Navigate Through the Fast-changing AI Landscape. Key Features - Access to industry-recognized AI methodology and deep learning mathematics with simple-to-understand examples. - Encompasses MDP Modeling, the Bellman Equation, Auto-regressive Models, BERT, and Transformers. - Detailed,...
BPB Publications, 2023. — 477 р. — ISBN: 978-93-5551-194-2. Mathematical Codebook to Navigate Through the Fast-changing AI Landscape. Key Features - Access to industry-recognized AI methodology and deep learning mathematics with simple-to-understand examples. - Encompasses MDP Modeling, the Bellman Equation, Auto-regressive Models, BERT, and Transformers. - Detailed,...
BPB Publications, 2023. — 477 р. — ISBN: 978-93-5551-194-2. Mathematical Codebook to Navigate Through the Fast-changing AI Landscape. Key Features - Access to industry-recognized AI methodology and deep learning mathematics with simple-to-understand examples. - Encompasses MDP Modeling, the Bellman Equation, Auto-regressive Models, BERT, and Transformers. - Detailed,...
CRC Press, 2022. — 267 p. — ISBN 978-1-032-06470-3. This book promotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of deep learning (DL)–based data analytics of IoT (Internet of Things) infrastructures. Deep Learning for Internet of Things Infrastructure addresses emerging trends and issues on IoT...
Amazon Digital Services, 2018. — 1750 p. People are using the tools of deep learning to change how we think about science, art, engineering, business, medicine, and even music. This book is for people who want to understand this field well enough to create deep learning systems, train them, and then use them with confidence to make their own contributions. The book takes a...
Digital Services LLC, 2018. — 910 p. — ASIN B079XSQNRX. People are using the tools of deep learning to change how we think about science, art, engineering, business, medicine, and even music. This book is for people who want to understand this field well enough to create deep learning systems, train them, and then use them with confidence to make their own contributions. The...
Digital Services LLC, 2018. — 914 p. — ASIN: B079Y1M81K. People are using the tools of deep learning to change how we think about science, art, engineering, business, medicine, and even music. This book is for people who want to understand this field well enough to create deep learning systems, train them, and then use them with confidence to make their own contributions. The...
Amazon Digital Services, 2018. — 1750 p. People are using the tools of deep learning to change how we think about science, art, engineering, business, medicine, and even music. This book is for people who want to understand this field well enough to create deep learning systems, train them, and then use them with confidence to make their own contributions. The book takes a...
No Starch Press, 2021. — 776 p. — ISBN 978-1718500723. A richly-illustrated, full-color introduction to deep learning that offers visual and conceptual explanations instead of equations. You'll learn how to use key deep learning algorithms without the need for complex math. Ever since computers began beating us at chess, they've been getting better at a wide range of human...
No Starch Press, 2021. — 776 p. — ISBN 978-1718500723. A richly-illustrated, full-color introduction to deep learning that offers visual and conceptual explanations instead of equations. You'll learn how to use key deep learning algorithms without the need for complex math. Ever since computers began beating us at chess, they've been getting better at a wide range of human...
No Starch Press, 2021. — 776 p. — ISBN 978-1718500723. A richly-illustrated, full-color introduction to deep learning that offers visual and conceptual explanations instead of equations. You'll learn how to use key deep learning algorithms without the need for complex math. Ever since computers began beating us at chess, they've been getting better at a wide range of human...
No Starch Press, 2021. — 776 p. — ISBN 978-1718500723. A richly-illustrated, full-color introduction to deep learning that offers visual and conceptual explanations instead of equations. You'll learn how to use key deep learning algorithms without the need for complex math. Ever since computers began beating us at chess, they've been getting better at a wide range of human...
MIT Press, 2016. — 802 p. — ISBN 978-0-262-33737-3. A comprehensive introduction to neural networks and deep learning by leading researchers of this field. Written for two main target audiences: university students (undergraduate or graduate) learning about machine learning, and software engineers. This is a PDF compilation of online book (www.deeplearningbook.org) Who Should...
MIT Press, 2016. — 802 p. — ISBN 978-0-262-33737-3. A comprehensive introduction to neural networks and deep learning by leading researchers of this field. Written for two main target audiences: university students (undergraduate or graduate) learning about machine learning, and software engineers. This is a PDF compilation of online book (www.deeplearningbook.org) Who Should...
MIT Press, 2016. — 802 p. — ISBN 978-0-262-33737-3. A comprehensive introduction to neural networks and deep learning by leading researchers of this field. Written for two main target audiences: university students (undergraduate or graduate) learning about machine learning, and software engineers. This is a PDF compilation of online book (www.deeplearningbook.org) Who Should...
MIT Press, 2016. — 802 p. — ISBN 978-0-262-33737-3. A comprehensive introduction to neural networks and deep learning by leading researchers of this field. Written for two main target audiences: university students (undergraduate or graduate) learning about machine learning, and software engineers. This is a PDF compilation of online book (www.deeplearningbook.org) Who Should...
MIT Press, 2016. — 802 p. — ISBN 978-0-262-33737-3. A comprehensive introduction to neural networks and deep learning by leading researchers of this field. Written for two main target audiences: university students (undergraduate or graduate) learning about machine learning, and software engineers. This is a PDF compilation of online book (www.deeplearningbook.org) Who Should...
Academic Press/Elsevier, 2023. — 270 p. — (Handbook of Statistics 48). — ISBN 9780443184314. Deep Learning, Volume 48 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timely topics, including Generative Adversarial Networks for Biometric Synthesis, Data Science and Pattern...
Academic Press/Elsevier, 2023. — 270 p. — (Handbook of Statistics 48). — ISBN 9780443184314. Deep Learning, Volume 48 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timely topics, including Generative Adversarial Networks for Biometric Synthesis, Data Science and Pattern...
Independently published, 2020. — 159 p. — ISBN B08NCGCC5M. Are you interested in Machine Learning? Are you fascinated by how robots work? Are you ready to open up to the dynamics of technological change? Machine Learning has been approached in a definitive manner as a subset falling under a larger set of Artificial intelligence . It majorly focuses on the aspect of learning of...
Independently published, 2020. — 159 p. — ISBN B08NCGCC5M. Are you interested in Machine Learning? Are you fascinated by how robots work? Are you ready to open up to the dynamics of technological change? Machine Learning has been approached in a definitive manner as a subset falling under a larger set of Artificial intelligence . It majorly focuses on the aspect of learning of...
Independently published, 2020. — 159 p. — ISBN B08NCGCC5M. Are you interested in Machine Learning? Are you fascinated by how robots work? Are you ready to open up to the dynamics of technological change? Machine Learning has been approached in a definitive manner as a subset falling under a larger set of Artificial intelligence . It majorly focuses on the aspect of learning of...
Apress Media LLC, 2022. — 395 p. — ISBN-13: 978-1-4842-8148-2. Optimize, develop, and design PyTorch and TensorFlow models for a specific problem using the Microsoft Neural Network Intelligence (NNI) toolkit. This book includes practical examples illustrating automated deep learning approaches and provides techniques to facilitate your deep learning model development. The first...
Apress Media LLC, 2023. — 396 p. — ISBN-13: 978-1-4842-8148-2. Optimize, develop, and design PyTorch and TensorFlow models for a specific problem using the Microsoft Neural Network Intelligence (NNI) toolkit. This book includes practical examples illustrating automated deep learning approaches and provides techniques to facilitate your deep learning model development. After...
Cambridge: Cambridge University Press, 2023. - 492 p. - ISBN 1316516784. In recent years the development of new classification and regression algorithms based on deep learning has led to a revolution in the fields of artificial intelligence, machine learning, and data analysis . The development of a theoretical foundation to guarantee the success of these algorithms constitutes...
Nova Science Publishers, Inc., 2023. — 140 p. Deep Learning has developed for more than 10 years. Many novel models are proposed. Among others, the attention models have greatly impacted the Deep Learning area. Similar to the attention mechanism of human beings, the attention mechanism improves the performance of many Deep Learning models based on its discovery of important...
BPB Publications, 2023. — 301 p. — ISBN: 978-93-5551-800-2. A step-by-step guide that will teach you how to deploy TinyML on microcontrollers. Key Features: - Deploy machine learning models on edge devices with ease. - Leverage pre-built AI models and deploy them without writing any code. - Create smart and efficient IoT solutions with TinyML. Description: TinyML, or Tiny...
BPB Publications, 2023. — 301 p. — ISBN: 978-93-5551-800-2. A step-by-step guide that will teach you how to deploy TinyML on microcontrollers. Key Features: - Deploy machine learning models on edge devices with ease. - Leverage pre-built AI models and deploy them without writing any code. - Create smart and efficient IoT solutions with TinyML. Description: TinyML, or Tiny...
BPB Publications, 2023. — 301 p. — ISBN 978-93-55518-057. A step-by-step guide that will teach you how to deploy TinyML on microcontrollers. Key Features: - Deploy machine learning models on edge devices with ease. - Leverage pre-built AI models and deploy them without writing any code. - Create smart and efficient IoT solutions with TinyML. Description: TinyML, or Tiny Machine...
Packt, 2019. — 328 p. — ISBN: 9781789805673. !Code files only Tackle the complex challenges faced while building end-to-end deep learning models using modern R libraries Learn Work with different datasets for image classification using CNNs Apply transfer learning to solve complex computer vision problems Use RNNs and their variants such as LSTMs and Gated Recurrent Units...
Packt, 2019. — 328 p. — ISBN: 9781789805673. Tackle the complex challenges faced while building end-to-end deep learning models using modern R libraries Learn Work with different datasets for image classification using CNNs Apply transfer learning to solve complex computer vision problems Use RNNs and their variants such as LSTMs and Gated Recurrent Units (GRUs) for sequence...
Packt, 2019. — 328 p. — ISBN: 9781789805673. Tackle the complex challenges faced while building end-to-end deep learning models using modern R libraries Learn Work with different datasets for image classification using CNNs Apply transfer learning to solve complex computer vision problems Use RNNs and their variants such as LSTMs and Gated Recurrent Units (GRUs) for sequence...
Packt, 2019. — 328 p. — ISBN: 9781789805673. Tackle the complex challenges faced while building end-to-end deep learning models using modern R libraries Learn Work with different datasets for image classification using CNNs Apply transfer learning to solve complex computer vision problems Use RNNs and their variants such as LSTMs and Gated Recurrent Units (GRUs) for sequence...
Packt Publishing Ltd., 2020. — 322 p. — ISBN: 978-1-78980-567-3. Tackle the complex challenges faced while building end-to-end deep learning models using modern R libraries Deep learning (DL) has evolved in recent years with developments such as generative adversarial networks (GANs), variational autoencoders (VAEs), and deep reinforcement learning. This book will get you up...
SciTech Publishing, 2021. — 897 p. — ISBN 978178561853. Novel deep learning approaches are achieving state-of-the-art accuracy in the area of radar target recognition, enabling applications beyond the scope of human-level performance. This book provides an introduction to the unique aspects of machine learning for radar signal processing that any scientist or engineer seeking...
SciTech Publishing, 2021. — 419 p.— ISBN 1785618520, 9781785618529. Novel deep learning approaches are achieving state-of-the-art accuracy in the area of radar target recognition, enabling applications beyond the scope of human-level performance. This book provides an introduction to the unique aspects of machine learning for radar signal processing that any scientist or...
Apress Media, LLC., 2022-12-31. — 239 p. — ISBN13: 978-1-4842-8587-9. Синтетические данные для глубокого обучения: создание синтетических данных для принятия решений и приложений с помощью Python и R Data is the indispensable fuel that drives the decision making of everything from governments, to major corporations, to sports teams. Its value is almost beyond measure. But what...
Apress Media, LLC., 2022-12-31. — 239 p. — ISBN13: 978-1-4842-8587-9. Синтетические данные для глубокого обучения: создание синтетических данных для принятия решений и приложений с помощью Python и R Data is the indispensable fuel that drives the decision making of everything from governments, to major corporations, to sports teams. Its value is almost beyond measure. But what...
Apress Media, LLC., 2022-12-31. — 239 p. — ISBN13: 978-1-4842-8587-9. Синтетические данные для глубокого обучения: создание синтетических данных для принятия решений и приложений с помощью Python и R Data is the indispensable fuel that drives the decision making of everything from governments, to major corporations, to sports teams. Its value is almost beyond measure. But what...
Apress Media, LLC., 2022-12-31. — 239 p. — ISBN-13 978-1-4842-8586-2. Синтетические данные для глубокого обучения: создание синтетических данных для принятия решений и приложений с помощью Python и R Data is the indispensable fuel that drives the decision making of everything from governments, to major corporations, to sports teams. Its value is almost beyond measure. But what...
Packt, 2022. — 188 p. — ISBN 9781801816823. Search is a big and ever-growing part of the tech ecosystem. Traditional search, however, has limitations that are hard to overcome because of the way it is designed. Neural search is a novel approach that uses the power of machine learning to retrieve information using vector embeddings as first-class citizens, opening up new...
Springer. 2023. — 249 p. Unlike most available sources that focus on deep neural network (DNN) inference, this book provides readers with a single-source reference on the needs, requirements, and challenges involved with on-device, DNN training semiconductor and SoC design. The authors include coverage of the trends and history surrounding the development of on-device DNN...
New York: Engineering Science Reference, 2019. — 374 p. Leading technology firms and research institutions are continuously exploring new techniques in artificial intelligence and machine learning. As such, deep learning has now been recognized in various real-world applications such as computer vision, image processing, biometrics, pattern recognition, and medical imaging. The...
IOS Press, 2017. — 284 p. Deep learning and image processing are two areas of great interest to academics and industry professionals alike. The areas of application of these two disciplines range widely, encompassing fields such as medicine, robotics, and security and surveillance. The aim of this book, ‘Deep Learning for Image Processing Applications’, is to offer concepts from...
Packt, 2019. — 612 p. — ISBN: 9781838642709. !Code files only Explore the world of neural networks by building powerful deep learning models using the R ecosystem Key Features Get to grips with the fundamentals of deep learning and neural networks Use R 3.5 and its libraries and APIs to build deep learning models for computer vision and text processing Implement effective deep...
Packt Publishing, 2018. — 378 p. — ISBN: 978-1788992893, ASIN 178899289X. Implement neural network models in R 3.5 using TensorFlow, Keras, and MXNet Key Features Use R 3.5 for building deep learning models for computer vision and text Apply deep learning techniques in cloud for large-scale processing Build, train, and optimize neural network models on a range of datasets Book...
Packt Publishing, 2018. — 378 p. — ISBN: 978-1788992893, ASIN 178899289X. Implement neural network models in R 3.5 using TensorFlow, Keras, and MXNet Key Features Use R 3.5 for building deep learning models for computer vision and text Apply deep learning techniques in cloud for large-scale processing Build, train, and optimize neural network models on a range of datasets Book...
Mong-Fong Horng, Hsu-Yang Kung, Chi-Hua Chen, Feng-Jang Hwang. — Mdpi AG, 2020. — 274 p. — ISBN: 978-3-03928-864-9. Machine Learning (ML) and Deep Learning (DL) techniques have been the crucial tools when it comes to the feature extracting and event estimating for developing applications in the electronics industries. Some techniques have been implemented in the embedded...
2018. — 132 p. — ISBN: 1727337964. Have you ever wanted to learn how to better use your data? Are you interested in the works of machine learning? If you answered yes to these questions, then this book is for you. Deep learning is a powerful data tool that can help improve businesses. In this book, you will learn: Neural networks Machine learning How it relates to certain...
2018. — 132 p. — ISBN: 1727337964. Have you ever wanted to learn how to better use your data? Are you interested in the works of machine learning? If you answered yes to these questions, then this book is for you. Deep learning is a powerful data tool that can help improve businesses. In this book, you will learn: Neural networks Machine learning How it relates to certain...
Cham: Springer International Publishing, 2019. — 168 p. — ISBN: 978-3-030-06073-2. The purpose of this edited volume is to provide a comprehensive overview on the fundamentals of deep learning, introduce the widely-used learning architectures and algorithms, present its latest theoretical progress, discuss the most popular deep learning platforms and data sets, and describe how...
Springer, 2022. — 117 p. — (Synthesis Lectures on Computer Vision). — ISBN 978-3-031-14594-0. Методы нормализации в глубоком обучении This book presents and surveys normalization techniques with a deep analysis in training deep neural networks. In addition, the author provides technical details in designing new normalization methods and network architectures tailored to...
Springer, 2022. — 117 p. — (Synthesis Lectures on Computer Vision). — ISBN 978-3-031-14594-0. Методы нормализации в глубоком обучении This book presents and surveys normalization techniques with a deep analysis in training deep neural networks. In addition, the author provides technical details in designing new normalization methods and network architectures tailored to...
Academic Press, 2021. — 353 p. — ISBN 978-0-323-90198-7. Principles and Labs for Deep Learning provides the knowledge and techniques needed to help readers design and develop deep learning models. Deep Learning techniques are introduced through theory, comprehensively illustrated, explained through the TensorFlow source code examples, and analyzed through the visualization of...
Academic Press, 2022. — 638 p. Deep Learning for Robot Perception and Cognition introduces a broad range of topics and methods in deep learning for robot perception and cognition together with end-to-end methodologies. The book provides the conceptual and mathematical background needed for approaching a large number of robot perception and cognition tasks from an end-to-end...
IGI Global, 2023. — 324. — (Advances in Finance, Accounting, and Economics (AFAE) Book Series). — ISBN 9781668444849. The advancements in Artificial Intelligence and Machine Learning have significantly affected the way financial services are offered and adopted today. Important financial decisions such as investment decision making, macroeconomic analysis, and credit evaluation...
IGI Global, 2020. — 1671 p. — ISBN: 978-1799804154. Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries. It is necessary to develop new techniques for managing data in order to ensure adequate usage. Deep learning, a subset of artificial intelligence and machine learning, has been recognized in...
IGI Global, 2020. — 1671 p. — ISBN: 978-1799804154. Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries. It is necessary to develop new techniques for managing data in order to ensure adequate usage. Deep learning, a subset of artificial intelligence and machine learning, has been recognized in...
IGI Global, 2020. — 1671 p. — ISBN: 978-1799804154. Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries. It is necessary to develop new techniques for managing data in order to ensure adequate usage. Deep learning, a subset of artificial intelligence and machine learning, has been recognized in...
IGI Global, 2020. — 1671 p. — ISBN: 978-1799804154. Due to the growing use of web applications and communication devices, the use of data has increased throughout various industries. It is necessary to develop new techniques for managing data in order to ensure adequate usage. Deep learning, a subset of artificial intelligence and machine learning, has been recognized in...
Packt Publishing, 2020. — 263 p. — ISBN: 978-1-83882-546-1. Get to grips with building powerful deep learning models using scikit-learn and Keras One-shot learning has been an active field of research for scientists trying to develop a cognitive machine that mimics human learning. As there are numerous theories about how humans perform one-shot learning, there are several...
Packt Publishing, 2020. — 263 p. — ISBN: 978-1-83882-546-1. Get to grips with building powerful deep learning models using scikit-learn and Keras One-shot learning has been an active field of research for scientists trying to develop a cognitive machine that mimics human learning. As there are numerous theories about how humans perform one-shot learning, there are several...
Packt Publishing, 2020. — 263 p. — ISBN: 978-1-83882-546-1. Get to grips with building powerful deep learning models using scikit-learn and Keras One-shot learning has been an active field of research for scientists trying to develop a cognitive machine that mimics human learning. As there are numerous theories about how humans perform one-shot learning, there are several...
Packt Publishing, 2020. — 145 p. — ISBN: 978-1-83882-546-1. Get to grips with building powerful deep learning models using scikit-learn and Keras One-shot learning has been an active field of research for scientists trying to develop a cognitive machine that mimics human learning. As there are numerous theories about how humans perform one-shot learning, there are several...
Packt Publishing, 2020. — 145 p. — ISBN: 978-1-83882-546-1. Code files only! Get to grips with building powerful deep learning models using scikit-learn and Keras One-shot learning has been an active field of research for scientists trying to develop a cognitive machine that mimics human learning. As there are numerous theories about how humans perform one-shot learning, there...
River Publishers, 2022. — 312 p. Health care today is known to suffer from siloed and fragmented data, delayed clinical communications, and disparate workflow tools due to the lack of interoperability caused by vendor-locked health care systems, lack of trust among data holders, and security/privacy concerns regarding data sharing. The health information industry is ready for...
New York: Springer, 2020. — 216 p. This book introduces readers to the fundamentals of deep neural network architectures, with a special emphasis on memristor circuits and systems. At first, the book offers an overview of neuro-memristive systems, including memristor devices, models, and theory, as well as an introduction to deep learning neural networks such as multi-layer...
Springer Nature Singapore Pte Ltd., 2019. — 237 p. — ISBN: 978-981-10-5151-7. This book discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and its...
Springer Nature Singapore Pte Ltd., 2019. — 237 p. — ISBN: 978-981-10-5152-4 (eBook). This book discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and...
Springer Nature Singapore Pte Ltd., 2019. — 237 p. — ISBN: 978-981-10-5152-4 (eBook). This book discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and...
Springer Nature Singapore Pte Ltd., 2019. — 237 p. — ISBN: 978-981-10-5152-4 (eBook). This book discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and...
Independently published, 2022. — 585 p. Composed for everyday programmers, there are no complicated mathematical proofs or unnecessary academic concept in Inside Deep Discovering . Trip with the theory and technique of modern deep learning, and also use ingenious methods to solve daily information issues. Inside Deep Understanding is a busy novice's guide to solving common...
Independently published, 2022. — 473 p. Computer system vision is main to several groundbreaking innovations, consisting of self-driving cars, drones, boosted truth, facial recognition, and a lot, much more . Incredible new computer system vision applications are created each day, thanks to fast developments in AI as well as deep learning (DL) . Deep Learning for Vision...
Springer, 2024. — 413 p. This book provides a systematic study on the security of Deep Learning. With its powerful learning ability, Deep Learning is widely used in CV, FL, GNN, RL, and other scenarios. However, during the process of application, researchers have revealed that Deep Learning is vulnerable to malicious attacks, which will lead to unpredictable consequences. Take...
Springer, 2023. — 432 p. — ISBN 3031328787. This book provides a conceptual understanding of deep learning algorithms. The book consists of the four parts: foundations, deep machine learning, deep neural networks, and textual deep learning. The first part provides traditional supervised learning, traditional unsupervised learning, and ensemble learning, as the preparation for...
Springer, 2023. — 433 p. — e-ISBN 978-3-031-32879-4. Основы глубокого обучения This book provides a conceptual understanding of Deep Learning algorithms. The book consists of the four parts: foundations, deep machine learning, deep neural networks, and textual deep learning. The first part provides traditional supervised learning, traditional unsupervised learning, and ensemble...
Birmingham: Packt Publishing, 2018. — 149 p. — ISBN: 1789534097. Key Features Clear and concise explanations. Gives important insights into deep learning models. Practical demonstration of key concepts. Book Description PyTorch is extremely powerful and yet easy to learn. It provides advanced features, such as supporting multiprocessor, distributed, and parallel computation ....
O’Reilly Media, Inc., 2024. — 350 р. — ISBN: 978-1-098-14839-3. Deep Learning is rapidly gaining momentum in the world of finance and trading. But for many professional traders, this sophisticated field has a reputation for being complex and difficult. This hands-on guide teaches you how to develop a deep learning trading model from scratch using Python, and it also helps you...
O’Reilly Media, Inc., 2024. — 350 р. — ISBN: 978-1-098-14839-3. Deep Learning is rapidly gaining momentum in the world of finance and trading. But for many professional traders, this sophisticated field has a reputation for being complex and difficult. This hands-on guide teaches you how to develop a deep learning trading model from scratch using Python, and it also helps you...
O’Reilly Media, Inc., 2024. — 350 р. — ISBN: 978-1-098-14839-3. Deep Learning is rapidly gaining momentum in the world of finance and trading. But for many professional traders, this sophisticated field has a reputation for being complex and difficult. This hands-on guide teaches you how to develop a deep learning trading model from scratch using Python, and it also helps you...
O’Reilly Media, Inc., 2024. — 350 р. — ISBN: 978-1-098-14839-3. Deep Learning is rapidly gaining momentum in the world of finance and trading. But for many professional traders, this sophisticated field has a reputation for being complex and difficult. This hands-on guide teaches you how to develop a deep learning trading model from scratch using Python, and it also helps you...
Springer, 2019. - 639 p. - ISBN: 3030145956. This textbook explains Deep Learning Architecture , with applications to various NLP Tasks, including Document Classification, Machine Translation, Language Modeling, and Speech Recognition. With the widespread adoption of deep learning, natural language processing (NLP),and speech applications in many areas (including Finance,...
3rd ed. — Birmingham: Packt Publishing, 2022. — 698 p. — ISBN 1803232919. Build cutting edge machine and deep learning systems for the lab, production, and mobile devices. Key Features Understand the fundamentals of deep learning and machine learning through clear explanations and extensive code samples. Implement graph neural networks, transformers using Hugging Face and...
Packt Publishing, 2018. — 436 p. — ISBN: 178899745X. Build and deploy powerful neural network models using the latest Java deep learning libraries Key Features Understand DL with Java by implementing real-world projects Master implementations of various ANN models and build your own DL systems Develop applications using NLP, image classification, RL, and GPU processing Book...
Packt Publishing, 2018. — 436 p. — ISBN: 178899745X. True PDF Build and deploy powerful neural network models using the latest Java deep learning libraries Key Features Understand DL with Java by implementing real-world projects Master implementations of various ANN models and build your own DL systems Develop applications using NLP, image classification, RL, and GPU processing...
Packt Publishing, 2018. — 496 p. — ISBN: 978-1-78899-745-4. Java Deep Learning Projects: Implement 10 real-world deep learning applications using Deeplearning4j and open source APIs Build and deploy powerful neural network models using the latest Java deep learning libraries Java is one of the most widely used programming languages. With the rise of deep learning, it has become...
Packt Publishing, 2018. — 496 p. — ISBN: 978-1-78899-745-4. Java Deep Learning Projects: Implement 10 real-world deep learning applications using Deeplearning4j and open source APIs Build and deploy powerful neural network models using the latest Java deep learning libraries Java is one of the most widely used programming languages. With the rise of deep learning, it has become...
IGI Global, 2017. — 265 p. — ISBN: 978-1522530152. The expansion of digital data has transformed various sectors of business such as healthcare, industrial manufacturing, and transportation. A new way of solving business problems has emerged through the use of machine learning techniques in conjunction with big data analytics. Deep Learning Innovations and Their Convergence...
Interviews AI. — 2020. — 411 p. — ISBN 9781916243569. Deep Learning Interviews is home to hundreds of fully-solved problems, from a wide range of key topics in AI. It is designed to both rehearse interview or exam specific topics and provide machine learning M.Sc./Ph.D. students, and those awaiting an interview a well-organized overview of the field. The problems it poses are...
BPB Publications, 2020. — 205 р. — ISBN: 978-93-89328-684. Learn modern-day technologies from modern-day technical giants DESCRIPTION The aim of this book is to help the readers understand the concept of artificial intelligence and deep learning methods and implement them into their businesses and organizations. The first two chapters describe the introduction of the artificial...
BPB Publications, 2020. — 205 р. — ISBN: 978-93-89328-684. Learn modern-day technologies from modern-day technical giants DESCRIPTION The aim of this book is to help the readers understand the concept of artificial intelligence and deep learning methods and implement them into their businesses and organizations. The first two chapters describe the introduction of the artificial...
BPB Publications, 2020. — 205 р. — ISBN: 978-93-89328-684. Learn modern-day technologies from modern-day technical giants DESCRIPTION The aim of this book is to help the readers understand the concept of artificial intelligence and deep learning methods and implement them into their businesses and organizations. The first two chapters describe the introduction of the artificial...
The MIT Press, 2019. — 296 p. — (MIT Press Essential Knowledge series). — ISBN: 9780262537551. An accessible introduction to the artificial intelligence technology that enables computer vision, speech recognition, machine translation, and driverless cars. Deep learning is an artificial intelligence technology that enables computer vision, speech recognition in mobile phones,...
The MIT Press, 2019. — 196 p. — (MIT Press Essential Knowledge series). — ISBN: 978-0262537551. An accessible introduction to the artificial intelligence technology that enables computer vision, speech recognition, machine translation, and driverless cars. Deep learning is an artificial intelligence technology that enables computer vision, speech recognition in mobile phones,...
The MIT Press, 2019. — 196 p. — (MIT Press Essential Knowledge series). — ISBN: 978-0262537551. An accessible introduction to the artificial intelligence technology that enables computer vision, speech recognition, machine translation, and driverless cars. Deep learning is an artificial intelligence technology that enables computer vision, speech recognition in mobile phones,...
The MIT Press, 2019. — 196 p. — (MIT Press Essential Knowledge series). — ISBN: 978-0262537551. An accessible introduction to the artificial intelligence technology that enables computer vision, speech recognition, machine translation, and driverless cars. Deep learning is an artificial intelligence technology that enables computer vision, speech recognition in mobile phones,...
2nd edition. — Apress, 2021. — 316 p. — ISBN 978-1484253632. Code files only! Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory and practice. This updated edition will prepare you for applying deep learning to real world problems with a sound theoretical foundation and practical know-how...
2nd edition. — Apress, 2021. — 316 p. — ISBN 978-1484253632. Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory and practice. This updated edition will prepare you for applying deep learning to real world problems with a sound theoretical foundation and practical know-how with PyTorch, a...
2nd edition. — Apress, 2021. — 316 p. — ISBN 978-1484253632. Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory and practice. This updated edition will prepare you for applying deep learning to real world problems with a sound theoretical foundation and practical know-how with PyTorch, a...
Apress, 2017. — 169 p. — ISBN: 978-1-4842-2765-7. Code files only! Discover the practical aspects of implementing deep-learning solutions using the rich Python ecosystem. This book bridges the gap between the academic state-of-the-art and the industry state-of-the-practice by introducing you to deep learning frameworks such as Keras, Theano, and Caffe. The practicalities of...
Apress, 2017. — 169 p. — ISBN: 978-1-4842-2765-7. Discover the practical aspects of implementing deep-learning solutions using the rich Python ecosystem. This book bridges the gap between the academic state-of-the-art and the industry state-of-the-practice by introducing you to deep learning frameworks such as Keras, Theano, and Caffe. The practicalities of these frameworks is...
Apress, 2017. — 169 p. — ISBN: 978-1-4842-2765-7. Discover the practical aspects of implementing deep-learning solutions using the rich Python ecosystem. This book bridges the gap between the academic state-of-the-art and the industry state-of-the-practice by introducing you to deep learning frameworks such as Keras, Theano, and Caffe. The practicalities of these frameworks is...
Apress, 2017. — 169 p. — ISBN: 978-1-4842-2765-7. Discover the practical aspects of implementing deep-learning solutions using the rich Python ecosystem. This book bridges the gap between the academic state-of-the-art and the industry state-of-the-practice by introducing you to deep learning frameworks such as Keras, Theano, and Caffe. The practicalities of these frameworks is...
Apress, 2017. — 169 p. — ISBN13: (electronic): 978-1-4842-2766-4. Discover the practical aspects of implementing deep-learning solutions using the rich Python ecosystem. This book bridges the gap between the academic state-of-the-art and the industry state-of-the-practice by introducing you to deep learning frameworks such as Keras, Theano, and Caffe. The practicalities of...
Apress, 2017. — 169 p. — ISBN13: (electronic): 978-1-4842-2766-4. Discover the practical aspects of implementing deep-learning solutions using the rich Python ecosystem. This book bridges the gap between the academic state-of-the-art and the industry state-of-the-practice by introducing you to deep learning frameworks such as Keras, Theano, and Caffe. The practicalities of...
CRC Press, 2023. — 414 р. — (The R Series). — ISBN: 978-1-032-23139-6. This is a book about torch, the R interface to PyTorch. PyTorch, as of this writing, is one of the major Deep Learning and scientific-computing frameworks, widely used across industries and areas of research. With torch, you get to access its rich functionality directly from R, with no need to install, let...
Leanpub, 2022. — 163 p. Zefs Guide to Deep Learning is a short guide to the most important concepts in Deep Learning, the technique at the center of the current Artificial Intelligence (AI) revolution. It will give you a strong understanding of the core ideas and most important methods and applications. All in around only 150 pages! This book presents the foundational concepts...
Leanpub, 2023-05-31. — 163 р. (2023-05-31 Update) Zefs Guide to Deep Learning is a short guide to the most important concepts in Deep Learning, the technique at the center of the current Artificial Intelligence (AI) revolution. It will give you a strong understanding of the core ideas and most important methods and applications. All in around only 150 pages! This book presents...
Leanpub, 2023-05-31. — 163 р. (2023-05-31 Update) Zefs Guide to Deep Learning is a short guide to the most important concepts in Deep Learning, the technique at the center of the current Artificial Intelligence (AI) revolution. It will give you a strong understanding of the core ideas and most important methods and applications. All in around only 150 pages! This book presents...
Leanpub, 2023-05-31. — 163 р. (2023-05-31 Update) Zefs Guide to Deep Learning is a short guide to the most important concepts in Deep Learning, the technique at the center of the current Artificial Intelligence (AI) revolution. It will give you a strong understanding of the core ideas and most important methods and applications. All in around only 150 pages! This book presents...
Leanpub, 2023-05-31. — 163 р. (2023-05-31 Update) Zefs Guide to Deep Learning is a short guide to the most important concepts in Deep Learning, the technique at the center of the current Artificial Intelligence (AI) revolution. It will give you a strong understanding of the core ideas and most important methods and applications. All in around only 150 pages! This book presents...
New York: Springer, 2019. — 93 p. This book presents deep learning techniques, concepts, and algorithms to classify and analyze big data. Further, it offers an introductory level understanding of the new programming languages and tools used to analyze big data in real-time, such as Hadoop, SPARK, and GRAPHX. Big data analytics using traditional techniques face various...
BPB Publications, 2024. — 544 p. A hands-on guide to building and deploying Deep Learning models with Python. Key Features: - Acquire the skills to perform exploratory data analysis, uncover insights, and preprocess data for Deep Learning tasks. - Build and train various types of neural networks, including Convolutional Neural Networks (CNNs) and Recurrent Neural Networks...
BPB Publications, 2024. — 544 р. — ISBN 978-93-55515-391. A hands-on guide to building and deploying Deep Learning models with Python. Key Features: - Acquire the skills to perform exploratory data analysis, uncover insights, and preprocess data for Deep Learning tasks. - Build and train various types of neural networks, including Convolutional Neural Networks (CNNs) and...
BPB Publications, 2024. — 544 р. — ISBN 978-93-55515-391. A hands-on guide to building and deploying Deep Learning models with Python. Key Features: - Acquire the skills to perform exploratory data analysis, uncover insights, and preprocess data for Deep Learning tasks. - Build and train various types of neural networks, including Convolutional Neural Networks (CNNs) and...
BPB Publications, 2024. — 544 р. — ISBN 978-93-55515-391. A hands-on guide to building and deploying Deep Learning models with Python. Key Features: - Acquire the skills to perform exploratory data analysis, uncover insights, and preprocess data for Deep Learning tasks. - Build and train various types of neural networks, including Convolutional Neural Networks (CNNs) and...
Elsevier, 2024. — 334 p. — ISBN: 978-0-443-21432-5. Applications of Deep Machine Learning in Future Energy Systems pushes the limits of current Artificial Intelligence techniques to present deep machine learning suitable for the complexity of sustainable energy systems. The first two chapters take the reader through the latest trends in power engineering and system design and...
Elsevier, 2024. — 334 p. — ISBN: 978-0-443-21432-5. Applications of Deep Machine Learning in Future Energy Systems pushes the limits of current Artificial Intelligence techniques to present deep machine learning suitable for the complexity of sustainable energy systems. The first two chapters take the reader through the latest trends in power engineering and system design and...
Elsevier, 2024. — 334 p. — ISBN: 978-0-443-21432-5. Applications of Deep Machine Learning in Future Energy Systems pushes the limits of current Artificial Intelligence techniques to present deep machine learning suitable for the complexity of sustainable energy systems. The first two chapters take the reader through the latest trends in power engineering and system design and...
Elsevier, 2024. — 334 p. — ISBN: 978-0-443-21432-5. Applications of Deep Machine Learning in Future Energy Systems pushes the limits of current Artificial Intelligence techniques to present deep machine learning suitable for the complexity of sustainable energy systems. The first two chapters take the reader through the latest trends in power engineering and system design and...
Singapore: Springer Singapor, 2018. — 79 p. — ISBN: 978-981-13-1444-5. This book presents recent advances in intrusion detection systems (IDSs) using state-of-the-art deep learning methods. It also provides a systematic overview of classical machine learning and the latest developments in deep learning. In particular, it discusses deep learning applications in IDSs in different...
Singapore: Springer Singapor, 2018. — 79 p. — ISBN: 978-981-13-1444-5. This book presents recent advances in intrusion detection systems (IDSs) using state-of-the-art deep learning methods. It also provides a systematic overview of classical machine learning and the latest developments in deep learning. In particular, it discusses deep learning applications in IDSs in different...
Apress, 2017. — 151 p. — ISBN: 978-1484228449. Get started with MatLAB for deep learning and AI with this in-depth primer. In this book, you start with machine learning fundamentals, then move on to neural networks, deep learning, and then convolutional neural networks. In a blend of fundamentals and applications, MatLAB Deep Learning employs MatLAB as the underlying...
New York: Apress, 2017. — 151 p. Get started with MatLAB for deep learning and AI with this in-depth primer. In this book, you start with machine learning fundamentals, then move on to neural networks, deep learning, and then convolutional neural networks. In a blend of fundamentals and applications, MatLAB Deep Learning employs MatLAB as the underlying programming language and...
3rd Edition. — De Gruyter, 2023. — 574 p. — (De Gruyter Textbook). — ISBN 978-3111028119. Reading the book, you can feel the long practical experience of the author. The text is easy to read, even where concepts can be complex. The strong theoretical background of the author is well known from other publications. In this book, however, the topics are presented on a level that...
No Starch Press, 2021. — 464 p. — ISBN-13: 978-1-7185-0075-4 (ebook). Practical Deep Learning teaches total beginners how to build the datasets and models needed to train neural networks for your own DL projects. If you’ve been curious about machine learning but didn’t know where to start, this is the book you’ve been waiting for. Focusing on the subfield of machine learning...
No Starch Press, 2021. — 464 p. — ISBN-13: 978-1-7185-0075-4 (ebook). Practical Deep Learning teaches total beginners how to build the datasets and models needed to train neural networks for your own DL projects. If you’ve been curious about machine learning but didn’t know where to start, this is the book you’ve been waiting for. Focusing on the subfield of machine learning...
No Starch Press, 2021. — 464 p. — ISBN 9781718500747. Practical Deep Learning teaches total beginners how to build the datasets and models needed to train neural networks for your own DL projects. If you’ve been curious about machine learning but didn’t know where to start, this is the book you’ve been waiting for. Focusing on the subfield of machine learning known as deep...
No Starch Press, 2021. — 464 p. — ISBN 9781718500747. Practical Deep Learning teaches total beginners how to build the datasets and models needed to train neural networks for your own DL projects. If you’ve been curious about machine learning but didn’t know where to start, this is the book you’ve been waiting for. Focusing on the subfield of machine learning known as deep...
No Starch Press, 2022. — 344 p. — ISBN 978-1-7185-0190-4. With Math for Deep Learning, you'll learn the essential mathematics used by and as a background for deep learning. You'll work through Python examples to learn key deep learning related topics in probability, statistics, linear algebra, differential calculus, and matrix calculus as well as how to implement data flow in a...
No Starch Press, 2022. — 344 p. — ISBN 978-1-7185-0190-4. With Math for Deep Learning, you'll learn the essential mathematics used by and as a background for deep learning. You'll work through Python examples to learn key deep learning related topics in probability, statistics, linear algebra, differential calculus, and matrix calculus as well as how to implement data flow in a...
No Starch Press, 2022. — 344 p. — ISBN 978-1-7185-0190-4. With Math for Deep Learning, you'll learn the essential mathematics used by and as a background for deep learning. You'll work through Python examples to learn key deep learning related topics in probability, statistics, linear algebra, differential calculus, and matrix calculus as well as how to implement data flow in a...
No Starch Press, 2022 — 347 p. Math for Deep Learning provides the essential math you need to understand deep learning discussions, explore more complex implementations, and better use the deep learning toolkits. With Math for Deep Learning, you'll learn the essential mathematics used by and as a background for deep learning. You’ll work through Python examples to learn key...
No Starch Press, 2022. — 344 p. — ISBN 978-1-7185-0190-4. With Math for Deep Learning, you'll learn the essential mathematics used by and as a background for deep learning. You'll work through Python examples to learn key deep learning related topics in probability, statistics, linear algebra, differential calculus, and matrix calculus as well as how to implement data flow in a...
Boca Raton: CRC Press, 2021. — 365 p. This book is a detailed reference on biomedical applications using Deep Learning. Because Deep Learning is an important actor shaping the future of Artificial Intelligence, its specific and innovative solutions for both medical and biomedical are very critical. This book provides a recent view of research works on essential, and?advanced...
Springer, 2021. — 732 p. — ISBN 978-3-030-77938-2. This book is used at the graduate or advanced undergraduate level and many others. Manned and unmanned ground, aerial and marine vehicles enable many promising and revolutionary civilian and military applications that will change our life in the near future. These applications include, but are not limited to, surveillance,...
O’Reilly Media, 2019. — 620 p. — ISBN: 978-1-492-03486-5. Whether you’re a software engineer aspiring to enter the world of deep learning, a veteran data scientist, or a hobbyist with a simple dream of making the next viral AI app, you might have wondered where to begin. This step-by-step guide teaches you how to build practical deep learning applications for the cloud, mobile,...
O’Reilly Media, 2019. — 620 p. — ISBN: 978-1-492-03486-5. Whether you’re a software engineer aspiring to enter the world of deep learning, a veteran data scientist, or a hobbyist with a simple dream of making the next viral AI app, you might have wondered where to begin. This step-by-step guide teaches you how to build practical deep learning applications for the cloud, mobile,...
O’Reilly Media, 2019. — 620 p. — ISBN: 978-1-492-03486-5. Whether you’re a software engineer aspiring to enter the world of deep learning, a veteran data scientist, or a hobbyist with a simple dream of making the next viral AI app, you might have wondered where to begin. This step-by-step guide teaches you how to build practical deep learning applications for the cloud, mobile,...
O’Reilly Media, 2019. — 620 p. — ISBN: 978-1-492-03486-5. Whether you’re a software engineer aspiring to enter the world of deep learning, a veteran data scientist, or a hobbyist with a simple dream of making the next viral AI app, you might have wondered where to begin. This step-by-step guide teaches you how to build practical deep learning applications for the cloud, mobile,...
Morgan & Claypool Publishers , 2020. - 164p. - ISBN: 1681738694 This Synthesis Lecture focuses on techniques for efficient data orchestration within DNN accelerators. The End of Moore's Law, coupled with the increasing growth in deep learning and other AI applications has led to the emergence of custom Deep Neural Network (DNN) accelerators for energy-efficient inference on...
Addison-Wesley Professional, 2019. — 871 p. — (Addison-Wesley Data & Analytics Series). — ISBN: 0135116694. Глубокое обучение - одна из самых горячих областей сегодняшнего дня. Такой подход к машинному обучению позволяет достичь прорывных результатов в некоторых из самых популярных приложений на сегодняшний день, в организациях от Google до Tesla, от Facebook до Apple. Тысячи...
Addison-Wesley Professional, 2020. — 415 p. — (Addison-Wesley Data & Analytics Series). — ISBN13: 978-0-13-511669-2. Deep learning is one of today’s hottest fields. This approach to machine learning is achieving breakthrough results in some of today’s highest profile applications, in organizations ranging from Google to Tesla, Facebook to Apple. Thousands of technical...
Addison-Wesley Professional, 2020. — 415 p. — (Addison-Wesley Data & Analytics Series). — ISBN13: 978-0-13-511669-2. Deep learning is one of today’s hottest fields. This approach to machine learning is achieving breakthrough results in some of today’s highest profile applications, in organizations ranging from Google to Tesla, Facebook to Apple. Thousands of technical...
Addison-Wesley Professional, 2020. — 415 p. — (Addison-Wesley Data & Analytics Series). — ISBN13: 978-0-13-511669-2. Deep learning is one of today’s hottest fields. This approach to machine learning is achieving breakthrough results in some of today’s highest profile applications, in organizations ranging from Google to Tesla, Facebook to Apple. Thousands of technical...
Addison-Wesley Professional, 2020. — 415 p. — (Addison-Wesley Data & Analytics Series). — ISBN13: 978-0-13-511669-2. Deep learning is one of today’s hottest fields. This approach to machine learning is achieving breakthrough results in some of today’s highest profile applications, in organizations ranging from Google to Tesla, Facebook to Apple. Thousands of technical...
Addison Wesley, 2018. — 320 р. — ISBN: 978-0135116692. Deep learning is one of today's hottest fields. This approach to machine learning is achieving breakthrough results in some of today's highest profile applications, in organizations ranging from Google to Tesla, Facebook to Apple. Thousands of technical professionals and students want to start leveraging its power, but...
CRC Press 2023. — 216 p. — eBook ISBN: 978-1-003-45632-2. This book covers the description of both conventional methods and advanced methods. In conventional methods, visual tracking techniques such as stochastic, deterministic, generative, and discriminative are discussed. The conventional techniques are further explored for multi-stage and collaborative frameworks. In...
CRC Press, 2023. — 246 р. — ISBN: 978-1-032-39166-3. Deep Learning Approach for Natural Language Processing, Speech, and Computer Vision provides an overview of general deep learning methodology and its applications of Natural Language Processing (NLP), speech and Computer Vision tasks. It simplifies and presents the concepts of Deep Learning in a comprehensive manner, with...
CRC Press, 2023. — 246 р. — ISBN: 978-1-003-34868-9. Deep Learning Approach for Natural Language Processing, Speech, and Computer Vision provides an overview of general deep learning methodology and its applications of Natural Language Processing (NLP), speech and Computer Vision tasks. It simplifies and presents the concepts of Deep Learning in a comprehensive manner, with...
CRC Press, 2023. — 246 р. — ISBN: 978-1-003-34868-9. Deep Learning Approach for Natural Language Processing, Speech, and Computer Vision provides an overview of general deep learning methodology and its applications of Natural Language Processing (NLP), speech and Computer Vision tasks. It simplifies and presents the concepts of Deep Learning in a comprehensive manner, with...
CRC Press, 2023. — 246 р. — ISBN: 978-1-003-34868-9. Deep Learning Approach for Natural Language Processing, Speech, and Computer Vision provides an overview of general deep learning methodology and its applications of Natural Language Processing (NLP), speech and Computer Vision tasks. It simplifies and presents the concepts of Deep Learning in a comprehensive manner, with...
Manning Publishing, 2019. — 240 p. — ISBN: 978-1617295560. GANs in Action teaches you how to build and train your own Generative Adversarial Networks, one of the most important innovations in deep learning. In this book, you’ll learn how to start building your own simple adversarial system as you explore the foundation of GAN architecture: the generator and discriminator...
Manning Publishing, 2019. — 240 p. — ISBN: 978-1617295560. GANs in Action teaches you how to build and train your own Generative Adversarial Networks, one of the most important innovations in deep learning. In this book, you’ll learn how to start building your own simple adversarial system as you explore the foundation of GAN architecture: the generator and discriminator...
Manning Publishing, 2019. — 240 p. — ISBN: 978-1617295560. GANs in Action teaches you how to build and train your own Generative Adversarial Networks, one of the most important innovations in deep learning. In this book, you’ll learn how to start building your own simple adversarial system as you explore the foundation of GAN architecture: the generator and discriminator...
Manning Publishing, 2019. — 240 p. — ISBN: 978-1617295560. GANs in Action teaches you how to build and train your own Generative Adversarial Networks, one of the most important innovations in deep learning. In this book, you'll learn how to start building your own simple adversarial system as you explore the foundation of GAN architecture: the generator and discriminator...
Manning Publishing, 2019. — 240 p. — ISBN: 978-1617295560. Code files only! GANs in Action teaches you how to build and train your own Generative Adversarial Networks, one of the most important innovations in deep learning. In this book, you’ll learn how to start building your own simple adversarial system as you explore the foundation of GAN architecture: the generator and...
CRC Press; Taylor & Francis Group, 2021. — 162 p. — (Chapman & Hall/CRC Machine Learning & Pattern Recognition). — ISBN 978-0367-64947-0. Глубокое обучение и лингвистическая репрезентация The application of deep learning methods to problems in natural language processing has generated significant progress across a wide range of natural language processing tasks. For some of...
LazyProgrammer, 2016. — 46 p. When we talk about modern deep learning, we are often not talking about vanilla neural networks - but newer developments, like using Autoencoders and Restricted Boltzmann Machines to do unsupervised pre-training. Deep neural networks suffer from the vanishing gradient problem, and for many years researchers couldn’t get around it - that is, until new...
LazyProgrammer, 2016. — 46 p. When we talk about modern deep learning, we are often not talking about vanilla neural networks - but newer developments, like using Autoencoders and Restricted Boltzmann Machines to do unsupervised pre-training. Deep neural networks suffer from the vanishing gradient problem, and for many years researchers couldn’t get around it - that is, until new...
LazyProgrammer, 2016. — 46 p. When we talk about modern deep learning, we are often not talking about vanilla neural networks - but newer developments, like using Autoencoders and Restricted Boltzmann Machines to do unsupervised pre-training. Deep neural networks suffer from the vanishing gradient problem, and for many years researchers couldn’t get around it - that is, until new...
LazyProgrammer, 2016. — 46 p. When we talk about modern deep learning, we are often not talking about vanilla neural networks - but newer developments, like using Autoencoders and Restricted Boltzmann Machines to do unsupervised pre-training. Deep neural networks suffer from the vanishing gradient problem, and for many years researchers couldn’t get around it - that is, until new...
Springer, 2019. — 188 p. — (Studies in Big Data 48). — ISBN: 978-3-030-01179-6. Deep Learning and Missing Data in Engineering Systems uses deep learning and swarm intelligence methods to cover missing data estimation in engineering systems. The missing data estimation processes proposed in the book can be applied in image recognition and reconstruction. To facilitate the...
Springer, 2018 (2019 Edition). — 188 p. Deep Learning and Missing Data in Engineering Systems discuss concepts and applications of artificial intelligence, specifically, deep learning. The artificial intelligence techniques that are studied include multilayer autoencoder networks and deep autoencoder networks. Also studied in this book are computational and swarm intelligence...
CreateSpace Independent Publishing Platform, 2016. — 251 p. — ISBN: 1519514212, 9781519514219 Master Deep Learning with this fun, practical, hands on guide. With the explosion of big data deep learning is now on the radar. Large companies such as Google, Microsoft, and Facebook have taken notice, and are actively growing in-house deep learning teams. Other large corporations...
New York: CreateSpace Independent Publishing Platform, 2016. — 212 p. Master Deep Time Series Forecasting with Python! Deep Time Series Forecasting with Python takes you on a gentle, fun and unhurried practical journey to creating deep neural network models for time series forecasting with Python. It uses plain language rather than mathematics; And is designed for working...
CRC, 2021. — 338 p. — ISBN: 9781536189896 Using the implementation of a deep learning framework as an example, C++ Template Metaprogramming in Practice: A Deep Learning Framework explains the application of metaprogramming in a relatively large project and emphasizes ways to optimize systems performance. The book is suitable for developers with a basic knowledge of C++....
World Scientific Publishing, 2024. — 493 p. — ISBN 978-981-12-8649-0. Глубокое обучение для 3D Vision: алгоритмы и приложения 3D Deep Learning is a rapidly evolving field that has the potential to transform various industries. This book provides a comprehensive overview of the current state-of-the-art in 3D Deep Learning, covering a wide range of research topics and...
Springer, 2020. — 160 p. — ISBN: 978-981-13-2386-7. This book introduces the applications of deep learning in various human centric visual analysis tasks, including classical ones like face detection and alignment and some newly rising tasks like fashion clothing parsing. Starting from an overview of current research in human centric visual analysis, the book then presents a...
CRC Press, 2025. — 408 p. — ISBN 978-1-032-72212-2. AlphaGo упрощенно: искусственный интеллект на основе правил и глубокое обучение в повседневных играх May 11, 1997, was a watershed moment in the history of artificial intelligence (AI): the IBM supercomputer chess engine, Deep Blue, beat the world Chess champion, Garry Kasparov. It was the first time a machine had triumphed...
Birmingham: Packt Publishing, 2022. — 287 p. — ISBN 1803241330. Train, test, run, track, store, tune, deploy, and explain provenance-aware deep learning models and pipelines at scale with reproducibility using MLflow. Key Features Focus on deep learning models and MLflow to develop practical business AI solutions at scale. Ship deep learning pipelines from experimentation to...
Packt Publishing Ltd., 2019. — 303 p. — ISBN: 978-1-78899-808-6. Concepts, tools, and techniques to explore deep learning architectures and methodologies Deep learning architectures are composed of multilevel nonlinear operations that represent high-level abstractions; this allows you to learn useful feature representations from the data. This book will help you learn and...
Packt Publishing Ltd., 2019. — 303 p. — ISBN: 978-1-78899-808-6. Concepts, tools, and techniques to explore deep learning architectures and methodologies Deep learning architectures are composed of multilevel nonlinear operations that represent high-level abstractions; this allows you to learn useful feature representations from the data. This book will help you learn and...
Packt Publishing Ltd., 2019. — 424 p. — ISBN: 978-1-78899-808-6. Concepts, tools, and techniques to explore deep learning architectures and methodologies Deep learning architectures are composed of multilevel nonlinear operations that represent high-level abstractions; this allows you to learn useful feature representations from the data. This book will help you learn and...
Packt Publishing Ltd., 2019. — 424 p. — ISBN: 978-1-78899-808-6. Concepts, tools, and techniques to explore deep learning architectures and methodologies Deep learning architectures are composed of multilevel nonlinear operations that represent high-level abstractions; this allows you to learn useful feature representations from the data. This book will help you learn and...
Packt Publishing Ltd., 2019. — 424 p. — ISBN: 978-1-78899-808-6. Concepts, tools, and techniques to explore deep learning architectures and methodologies Deep learning architectures are composed of multilevel nonlinear operations that represent high-level abstractions; this allows you to learn useful feature representations from the data. This book will help you learn and...
Packt Publishing Ltd., 2019. — 303 p. — ISBN: 978-1-78899-808-6. Code files only! Concepts, tools, and techniques to explore deep learning architectures and methodologies Deep learning architectures are composed of multilevel nonlinear operations that represent high-level abstractions; this allows you to learn useful feature representations from the data. This book will help...
New York: John Wiley & Sons, 2018. — 53 p. Are you looking for information to help you with your artificial intelligence deep learning journey? This Deep Learning Dummies guide will help you understand what AI, deep learning and machine learning can mean for you and your organization.
Springer Nature, 2019. — 452 p. — ISBN: 978-3-319-42999-1. This book reviews the state of the art in deep learning approaches to high-performance robust disease detection, robust and accurate organ segmentation in medical image computing (radiological and pathological imaging modalities), and the construction and mining of large-scale radiology databases. It particularly...
Springer Nature, 2019. — 452 p. — ISBN: 978-3-030-13969-8 (eBook). This book reviews the state of the art in deep learning approaches to high-performance robust disease detection, robust and accurate organ segmentation in medical image computing (radiological and pathological imaging modalities), and the construction and mining of large-scale radiology databases. It...
Springer Nature, 2019. — 452 p. — ISBN: 978-3-030-13969-8 (eBook). This book reviews the state of the art in deep learning approaches to high-performance robust disease detection, robust and accurate organ segmentation in medical image computing (radiological and pathological imaging modalities), and the construction and mining of large-scale radiology databases. It...
Springer Nature, 2019. — 452 p. — ISBN: 978-3-030-13969-8 (eBook). This book reviews the state of the art in deep learning approaches to high-performance robust disease detection, robust and accurate organ segmentation in medical image computing (radiological and pathological imaging modalities), and the construction and mining of large-scale radiology databases. It...
Cambridge University Press, 2021. — 339 p. — ISBN 978-1-108-83174-1. Deep learning on graphs has become one of the hottest topics in machine learning. The book consists of four parts to best accommodate our readers with diverse backgrounds and purposes of reading. Part 1 introduces basic concepts of graphs and deep learning; Part 2 discusses the most established methods from...
Editora Dialetica, 2022. — 121 p. Recently, Deep Learning has caused a significant impact on computer vision, speech recognition, and natural language understanding. In spite of the remarkable advances, Deep Learning (DL) recent performance gains have been modest and usually rely on increasing the depth of the models, which often requires more computational resources such as...
Artech House, 2020. — 313 p. — ISBN 978-1-63081--637-7. This authoritative resource presents a comprehensive illustration of modern Artificial Intelligence / Machine Learning (AI/ML) technology for radio frequency (RF) data exploitation. It identifies technical challenges, benefits, and directions of deep learning (DL) based object classification using radar data, including...
O’Reilly Media, Inc., 2024. — 458 p. — ISBN 978-1-098-14528-6. Bringing a deep-learning project into production at scale is quite challenging. To successfully scale your project, a foundational understanding of full stack deep learning, including the knowledge that lies at the intersection of hardware, software, data, and algorithms, is required. This book illustrates complex...
O’Reilly Media, Inc., 2024. — 458 p. — ISBN 978-1-098-14528-6. Bringing a deep-learning project into production at scale is quite challenging. To successfully scale your project, a foundational understanding of full stack deep learning, including the knowledge that lies at the intersection of hardware, software, data, and algorithms, is required. This book illustrates complex...
O’Reilly Media, Inc., 2024. — 458 p. — ISBN 978-1-098-14528-6. Bringing a deep-learning project into production at scale is quite challenging. To successfully scale your project, a foundational understanding of full stack deep learning, including the knowledge that lies at the intersection of hardware, software, data, and algorithms, is required. This book illustrates complex...
O’Reilly, 2024. — 448 p. — ISBN 978-1-098-14528-6. Bringing a deep-learning project into production at scale is quite challenging. To successfully scale your project, a foundational understanding of full stack deep learning, including the knowledge that lies at the intersection of hardware, software, data, and algorithms, is required. This book illustrates complex concepts of...
Hoboken: Wiley, 2024. — 405 p. An engaging and accessible introduction to Deep Learning perfect for students and professionals. In Deep Learning: A Practical Introduction, a team of distinguished researchers delivers a book complete with coverage of the theoretical and practical elements of Deep Learning. The book includes extensive examples, end-of-chapter exercises, homework,...
Apress, 2018. — 184 p. — ISBN: 148423720X. Discover the essential building blocks of a common and powerful form of deep belief network: convolutional nets. This book shows you how the structure of these elegant models is much closer to that of human brains than traditional neural networks; they have a ‘thought process’ that is capable of learning abstract concepts built from...
Apress, 2018. — 184 p. — ISBN: 148423720X. Discover the essential building blocks of a common and powerful form of deep belief network: convolutional nets. This book shows you how the structure of these elegant models is much closer to that of human brains than traditional neural networks; they have a ‘thought process’ that is capable of learning abstract concepts built from...
New York: Apress, 2018. — 262 p. This book is a continuation of Volume I of this series. Extensive references are made to material in that volume. For this reason, it is strongly suggested that you be at least somewhat familiar with the material in Volume I. All techniques presented in this book are given modest mathematical justification, including the equations relevant to...
Apress, 2018. — 262 p. — ISBN13: (electronic): 978-1-4842-3646-8. Discover the essential building blocks of a common and powerful form of deep belief net: the autoencoder. You’ll take this topic beyond current usage by extending it to the complex domain for signal and image processing applications. Deep Belief Nets in C++ and CUDA C: Volume 2 also covers several algorithms for...
Apress, 2018. — 262 p. — ISBN13: (electronic): 978-1-4842-3646-8. Discover the essential building blocks of a common and powerful form of deep belief net: the autoencoder. You’ll take this topic beyond current usage by extending it to the complex domain for signal and image processing applications. Deep Belief Nets in C++ and CUDA C: Volume 2 also covers several algorithms for...
Apress, 2018. — 262 p. — ISBN13: (electronic): 978-1-4842-3646-8. Discover the essential building blocks of a common and powerful form of deep belief net: the autoencoder. You’ll take this topic beyond current usage by extending it to the complex domain for signal and image processing applications. Deep Belief Nets in C++ and CUDA C: Volume 2 also covers several algorithms for...
Apress, 2018. — 165 p. — ISBN13: (electronic): 978-1-4842-3721-2. Discover the essential building blocks of a common and powerful form of deep belief network: convolutional nets. This book shows you how the structure of these elegant models is much closer to that of human brains than traditional neural networks; they have a ‘thought process’ that is capable of learning abstract...
Apress, 2018. — 165 p. — ISBN13: (electronic): 978-1-4842-3721-2. Discover the essential building blocks of a common and powerful form of deep belief network: convolutional nets. This book shows you how the structure of these elegant models is much closer to that of human brains than traditional neural networks; they have a ‘thought process’ that is capable of learning abstract...
Apress, 2018. — 200 p. — ISBN13: (electronic): 978-1-4842-3591-1. Discover the essential building blocks of the most common forms of deep belief networks. At each step this book provides intuitive motivation, a summary of the most important equations relevant to the topic, and concludes with highly commented code for threaded computation on modern CPUs as well as massive...
Apress, 2018. — 200 p. — ISBN13: (electronic): 978-1-4842-3591-1. Discover the essential building blocks of the most common forms of deep belief networks. At each step this book provides intuitive motivation, a summary of the most important equations relevant to the topic, and concludes with highly commented code for threaded computation on modern CPUs as well as massive...
Apress, 2018. — 219 p. Discover the essential building blocks of the most common forms of deep belief networks. At each step this book provides intuitive motivation, a summary of the most important equations relevant to the topic, and concludes with highly commented code for threaded computation on modern CPUs as well as massive parallel processing on computers with...
Apress, 2018. — 219 p. Discover the essential building blocks of the most common forms of deep belief networks. At each step this book provides intuitive motivation, a summary of the most important equations relevant to the topic, and concludes with highly commented code for threaded computation on modern CPUs as well as massive parallel processing on computers with...
ITexLi, 2021. — 192 p. — ISBN 9781839623752. This volume is dedicated to deep learning - a branch of machine learning similar to artificial intelligence. The applications of deep learning vary from medical imaging to industrial quality checking, sports, and precision agriculture. The book is divided into two sections. The first section covers deep learning architectures and the...
CRC Press, 2024. — 199 p. — ISBN 9781032487960. Глубокое обучение: руководство для начинающих This book focuses on Deep Learning (DL), which is an important aspect of Data Science, that includes predictive modeling. DL applications are widely used in domains such as finance, transport, healthcare, automanufacturing, and advertising. The design of the DL models based on...
CRC Press, 2024. — 199 p. — ISBN 9781032487960. Глубокое обучение: руководство для начинающих This book focuses on Deep Learning (DL), which is an important aspect of Data Science, that includes predictive modeling. DL applications are widely used in domains such as finance, transport, healthcare, automanufacturing, and advertising. The design of the DL models based on...
Anita Gehlot, Dolly Sharma, Monika Mangla, Rajesh Singh, Sergio Márquez Sánchez, Vaishali Mehta. — Bentham Science Publishers, 2022. — 228 p. — ISBN: 978-981-5036-08-4. The competence of deep learning for the automation and manufacturing sector has received astonishing attention in recent times. The manufacturing industry has recently experienced a revolutionary advancement...
Anita Gehlot, Dolly Sharma, Monika Mangla, Rajesh Singh, Sergio Márquez Sánchez, Vaishali Mehta. — Bentham Science Publishers, 2022. — 228 p. — ISBN: 978-981-5036-08-4. The competence of deep learning for the automation and manufacturing sector has received astonishing attention in recent times. The manufacturing industry has recently experienced a revolutionary advancement...
Anita Gehlot, Dolly Sharma, Monika Mangla, Rajesh Singh, Sergio Márquez Sánchez, Vaishali Mehta. — Bentham Science Publishers, 2022. — 228 p. — ISBN: 978-981-5036-08-4. The competence of deep learning for the automation and manufacturing sector has received astonishing attention in recent times. The manufacturing industry has recently experienced a revolutionary advancement...
Anita Gehlot, Dolly Sharma, Monika Mangla, Rajesh Singh, Sergio Márquez Sánchez, Vaishali Mehta. — Bentham Science Publishers, 2022. — 228 p. — ISBN: 978-981-5036-08-4. The competence of deep learning for the automation and manufacturing sector has received astonishing attention in recent times. The manufacturing industry has recently experienced a revolutionary advancement...
Packt Publishing, 2020. — 384 p. — ISBN 978-1-80056-661-3. Discover how to integrate KNIME Analytics Platform with deep learning libraries to implement artificial intelligence solutions Key Features - Become well-versed with KNIME Analytics Platform to perform codeless deep learning - Design and build deep learning workflows quickly and more easily using the KNIME GUI -...
Packt Publishing, 2020. — 384 p. — ISBN 978-1-80056-661-3. Discover how to integrate KNIME Analytics Platform with deep learning libraries to implement artificial intelligence solutions Key Features - Become well-versed with KNIME Analytics Platform to perform codeless deep learning - Design and build deep learning workflows quickly and more easily using the KNIME GUI -...
Packt Publishing, 2020. — 384 p. — ISBN 978-1-80056-661-3. Discover how to integrate KNIME Analytics Platform with deep learning libraries to implement artificial intelligence solutions Key Features - Become well-versed with KNIME Analytics Platform to perform codeless deep learning - Design and build deep learning workflows quickly and more easily using the KNIME GUI -...
Packt Publishing, 2020. — 384 p. — ISBN 978-1-80056-661-3. Discover how to integrate KNIME Analytics Platform with deep learning libraries to implement artificial intelligence solutions Key Features - Become well-versed with KNIME Analytics Platform to perform codeless deep learning - Design and build deep learning workflows quickly and more easily using the KNIME GUI -...
Packt, 2018. — 442 p. — ISBN: 978-1-78839-990-6 Deep learning is a popular subset of machine learning, and it allows you to build complex models that are faster and give more accurate predictions. This book is your companion to take your first steps into the world of deep learning, with hands-on examples to boost your understanding of the topic. This book starts with a quick...
Packt, 2018. — 442 p. — ISBN: 978-1-78839-990-6 Deep learning is a popular subset of machine learning, and it allows you to build complex models that are faster and give more accurate predictions. This book is your companion to take your first steps into the world of deep learning, with hands-on examples to boost your understanding of the topic. This book starts with a quick...
Apress, 2019. — 294 p. — ISBN: 1484249755. Develop and optimize deep learning models with advanced architectures. This book teaches you the intricate details and subtleties of the algorithms that are at the core of convolutional neural networks. In Advanced Applied Deep Learning, you will study advanced topics on CNN and object detection using Keras and TensorFlow. Along the...
Apress, 2019. — 294 p. — ISBN: 1484249755. Develop and optimize deep learning models with advanced architectures. This book teaches you the intricate details and subtleties of the algorithms that are at the core of convolutional neural networks. In Advanced Applied Deep Learning, you will study advanced topics on CNN and object detection using Keras and TensorFlow. Along the...
Apress, 2018. — 425 p. — ISBN: 1484237897. Code files only! Work with advanced topics in deep learning, such as optimization algorithms, hyper-parameter tuning, dropout, and error analysis as well as strategies to address typical problems encountered when training deep neural networks. You’ll begin by studying the activation functions mostly with a single neuron (ReLu, sigmoid,...
Apress, 2018. — 425 p. — ISBN: 1484237897. Work with advanced topics in deep learning, such as optimization algorithms, hyper-parameter tuning, dropout, and error analysis as well as strategies to address typical problems encountered when training deep neural networks. You’ll begin by studying the activation functions mostly with a single neuron (ReLu, sigmoid, and Swish),...
Apress, 2018. — 425 p. — ISBN: 1484237897. Work with advanced topics in deep learning, such as optimization algorithms, hyper-parameter tuning, dropout, and error analysis as well as strategies to address typical problems encountered when training deep neural networks. You’ll begin by studying the activation functions mostly with a single neuron (ReLu, sigmoid, and Swish),...
Apress, 2022. - 397p. - ISBN: 1484280199 Understand how neural networks work and learn how to implement them using TensorFlow 2.0 and Keras. This new edition focuses on the fundamental concepts and at the same time on practical aspects of implementing neural networks and deep learning for your research projects. This book is designed so that you can focus on the parts you are...
Apress, 2018. — 425 p. — ISBN13: 978-1-4842-3790-8. Work with advanced topics in deep learning, such as optimization algorithms, hyper-parameter tuning, dropout, and error analysis as well as strategies to address typical problems encountered when training deep neural networks. You'll begin by studying the activation functions mostly with a single neuron (ReLu, sigmoid, and...
Apress, 2018. — 425 p. — ISBN13: 978-1-4842-3790-8. Work with advanced topics in deep learning, such as optimization algorithms, hyper-parameter tuning, dropout, and error analysis as well as strategies to address typical problems encountered when training deep neural networks. You'll begin by studying the activation functions mostly with a single neuron (ReLu, sigmoid, and...
Gistrup: River Publishers, 2023. — 286 p. Object detection is a basic visual identification problem in computer vision that has been explored extensively over the years. Visual object detection seeks to discover objects of specific target classes in a given image with pinpoint accuracy and apply a class label to each object instance. Object recognition strategies based on deep...
2nd ed. — Packt, 2017. — 501 p. — ISBN: 978-1787125933. Unlock modern machine learning and deep learning techniques with Python by using the latest cutting-edge open source Python libraries. About This Book Second edition of the bestselling book on Machine Learning A practical approach to key frameworks in data science, machine learning, and deep learning Use the most powerful...
Springer, 2022. — 171 p. — (T-Labs Series in Telecommunication Services). — ISBN-13 9783030914783. This book presents how to apply recent machine learning (deep learning) methods for the task of speech quality prediction. The author shows how recent advancements in machine learning can be leveraged for the task of speech quality prediction and provides an in-depth analysis of...
Springer, 2023. — 215 p. This book covers various, leading-edge deep learning technologies. The author discusses new applications of deep learning and gives insight into the integration of deep learning with various application domains, such as autonomous driving, augmented reality, AIOT, 5G and beyond.
3rd ed. — Packt, 2020. — 495 p. — ISBN: 978-1800562967. Discover how to leverage Keras, the powerful and easy-to-use open-source Python library for developing and evaluating deep learning models Key Features Get to grips with various model evaluation metrics, including sensitivity, specificity, and AUC scores Explore advanced concepts such as sequential memory and sequential...
2nd Edition. — Packt Publishing, 2020. — 444 p. — ISBN: 978-1-83921-757-9. Code files only! Cut through the noise and get real results with a step-by-step approach to understanding deep learning with Keras programming You already know that you want to learn Keras, and a smarter way to learn is to learn by doing. The Deep Learning with Keras Workshop focuses on building up your...
Fullstack.io, 2020. — 769 p. Zero to Deep Learning is carefully designed to teach you step-by-step how to build, train, evaluate, improve and deploy deep learning models. Each chapter covers a topic and we provide full code examples as executable Jupyter notebooks. Within the first few minutes, we’ll know enough deep learning to start seeing the benefits of using it in our...
Fullstack.io, 2020. — 769 p. Zero to Deep Learning is carefully designed to teach you step-by-step how to build, train, evaluate, improve and deploy deep learning models. Each chapter covers a topic and we provide full code examples as executable Jupyter notebooks. Within the first few minutes, we’ll know enough deep learning to start seeing the benefits of using it in our...
Fullstack.io, 2020. — 769 p. Zero to Deep Learning is carefully designed to teach you step-by-step how to build, train, evaluate, improve and deploy deep learning models. Each chapter covers a topic and we provide full code examples as executable Jupyter notebooks. Within the first few minutes, we’ll know enough deep learning to start seeing the benefits of using it in our...
Fullstack.io, 2020. — 769 p. Zero to Deep Learning is carefully designed to teach you step-by-step how to build, train, evaluate, improve and deploy deep learning models. Each chapter covers a topic and we provide full code examples as executable Jupyter notebooks. Within the first few minutes, we’ll know enough deep learning to start seeing the benefits of using it in our...
Fullstack.io, 2020. — 769 p. Code files only! Zero to Deep Learning is carefully designed to teach you step-by-step how to build, train, evaluate, improve and deploy deep learning models. Each chapter covers a topic and we provide full code examples as executable Jupyter notebooks. Within the first few minutes, we’ll know enough deep learning to start seeing the benefits of...
Canada: John Wiley & Sons, Inc, 2019. — 442 p. — ISBN: 978-1-119-54304-6. Take a deep dive into deep learning. Deep learning provides the means for discerning patterns in the data that drive online business and social media outlets. Deep Learning for Dummies gives you the information you need to take the mystery out of the topic—and all of the underlying technologies associated...
John Wiley & Sons, Inc, 2019. — 442 p. — ISBN: 978-1-119-54304-6. Take a deep dive into deep learning. Deep learning provides the means for discerning patterns in the data that drive online business and social media outlets. Deep Learning for Dummies gives you the information you need to take the mystery out of the topic—and all of the underlying technologies associated with...
John Wiley & Sons, Inc, 2019. — 442 p. — ISBN: 978-1-119-54304-6. Take a deep dive into deep learning. Deep learning provides the means for discerning patterns in the data that drive online business and social media outlets. Deep Learning for Dummies gives you the information you need to take the mystery out of the topic—and all of the underlying technologies associated with...
John Wiley & Sons, Inc, 2019. — 442 p. — ISBN: 9781119543046. Take a deep dive into deep learning. Deep learning provides the means for discerning patterns in the data that drive online business and social media outlets. Deep Learning for Dummies gives you the information you need to take the mystery out of the topic—and all of the underlying technologies associated with it. In...
Leanpub, 2022. — 364 p. Version: 2022-10-03 Build Deep Learning applications with Keras and TensorFlow. Topics covered include Convolutional Neural networks, Recurrent Neural Networks, TensorBoard, Transfer learning, custom training loops, and Keras Functional API. Deep Learning (DL) is a branch of Machine Learning (ML) that involves building networks that try to mimic the...
Leanpub, 2022. — 364 p. Version: 2022-10-03 Build Deep Learning applications with Keras and TensorFlow. Topics covered include Convolutional Neural networks, Recurrent Neural Networks, TensorBoard, Transfer learning, custom training loops, and Keras Functional API. Deep Learning (DL) is a branch of Machine Learning (ML) that involves building networks that try to mimic the...
Amazon Digital Services LLC, 2017. — 75 p. — ISBN: 1981614060. Neural Networks and Deep Learning: Deep Learning explained to your granny – A visual introduction for beginners who want to make their own Deep Learning Neural Network (Machine Learning) Ready to crank up a neural network to get your self-driving car pick up the kids from school? Want to add 'Deep Learning’ to your...
Amazon Digital Services LLC, 2017. — 75 p. — ISBN: 1981614060. Neural Networks and Deep Learning: Deep Learning explained to your granny – A visual introduction for beginners who want to make their own Deep Learning Neural Network (Machine Learning) Ready to crank up a neural network to get your self-driving car pick up the kids from school? Want to add 'Deep Learning’ to your...
Amazon Digital Services LLC, 2017. — 75 p. — ISBN: 1981614060. Neural Networks and Deep Learning: Deep Learning explained to your granny – A visual introduction for beginners who want to make their own Deep Learning Neural Network (Machine Learning) Ready to crank up a neural network to get your self-driving car pick up the kids from school? Want to add 'Deep Learning’ to your...
Amazon Digital Services LLC, 2017. — 75 p. — ISBN: 1981614060. Neural Networks and Deep Learning: Deep Learning explained to your granny – A visual introduction for beginners who want to make their own Deep Learning Neural Network (Machine Learning) Ready to crank up a neural network to get your self-driving car pick up the kids from school? Want to add 'Deep Learning’ to your...
Loris Nanni, Sheryl Brahnam, Rick Brattin, Stefano Ghidoni, Lakhmi C. Jain. (Editors) — Springer, 2020. — 286 p. — ISBN: 978-3-030-42748-1. This book introduces readers to the current trends in using deep learners and deep learner descriptors for medical applications. It reviews the recent literature and presents a variety of medical image and sound applications to illustrate...
Loris Nanni, Sheryl Brahnam, Rick Brattin, Stefano Ghidoni, Lakhmi C. Jain. (Editors) — Springer, 2020. — 286 p. — ISBN: 978-3-030-42750-4 (eBook). This book introduces readers to the current trends in using deep learners and deep learner descriptors for medical applications. It reviews the recent literature and presents a variety of medical image and sound applications to...
Loris Nanni, Sheryl Brahnam, Rick Brattin, Stefano Ghidoni, Lakhmi C. Jain. (Editors). — Springer, 2020. — 286 p. — ISBN: 978-3-030-42750-4. This book introduces readers to the current trends in using deep learners and deep learner descriptors for medical applications. It reviews the recent literature and presents a variety of medical image and sound applications to illustrate...
Loris Nanni, Sheryl Brahnam, Rick Brattin, Stefano Ghidoni, Lakhmi C. Jain. (Editors) — Springer, 2020. — 286 p. — ISBN: 978-3-030-42750-4 (eBook). This book introduces readers to the current trends in using deep learners and deep learner descriptors for medical applications. It reviews the recent literature and presents a variety of medical image and sound applications to...
Morgan & Claypool, 2020. — 199 p. — ISBN: 9781681737607. Text production has many applications. It is used, for instance, to generate dialogue turns from dialogue moves, verbalise the content of knowledge bases, or generate English sentences from rich linguistic representations, such as dependency trees or abstract meaning representations. Text production is also at work in...
Springer, 2021. — 354 p. — ISBN 978-3-030-75177-7. This is the first book on synthetic data for deep learning, and its breadth of coverage may render this book as the default reference on synthetic data for years to come. The book can also serve as an introduction to several other important subfields of machine learning that are seldom touched upon in other books. Machine...
Springer, 2021. — 354 p. — ISBN 978-3-030-75177-7. This is the first book on synthetic data for deep learning, and its breadth of coverage may render this book as the default reference on synthetic data for years to come. The book can also serve as an introduction to several other important subfields of machine learning that are seldom touched upon in other books. Machine...
Cambridge University Press, 2011. — 540 p. The theme of this book is that human beings possess cognitive processes that enable them to override the imperatives of past experience and to act and think in novel ways, and that these processes differ from the types of cognitive processes usually envisioned in psychological theories of learning. The capability for what I call deep...
O’Reilly, 2018. — 220 p. — ISBN: 149199584X. Deep learning doesn't have to be intimidating. Until recently, this machine-learning method required years of study, but with frameworks such as Keras and Tensorflow, software engineers without a background in machine learning can quickly enter the field. With the recipes in this cookbook, you'll learn how to solve deep-learning...
CRC Press, 2022. — 274 p. — eBook ISBN 978-1-003-21514-1. The rise in living standards increases the expectation of people in almost every field. At the forefront is health. Over the past few centuries, there have been major developments in healthcare. Medical device technology and developments in artificial intelligence (AI) are among the most important ones. The improving...
Apress, 2018. — 290 p. — ISBN: 148423684X. Discover the concepts of deep learning used for natural language processing (NLP), with full-fledged examples of neural network models such as recurrent neural networks, long short-term memory networks, and sequence-2-sequence models. You’ll start by covering the mathematical prerequisites and the fundamentals of deep learning and NLP...
Apress, 2018. — 290 p. — ISBN: 148423684X. Discover the concepts of deep learning used for natural language processing (NLP), with full-fledged examples of neural network models such as recurrent neural networks, long short-term memory networks, and sequence-2-sequence models. You’ll start by covering the mathematical prerequisites and the fundamentals of deep learning and NLP...
Apress, 2018. — 290 p. — ISBN: 148423684X. Code files only! Discover the concepts of deep learning used for natural language processing (NLP), with full-fledged examples of neural network models such as recurrent neural networks, long short-term memory networks, and sequence-2-sequence models. You’ll start by covering the mathematical prerequisites and the fundamentals of deep...
Packt, 2022. — 321 p. — ISBN 180324366X. Supercharge your skills for tailoring deep-learning models and deploying them in production environments with ease and precision. Key Features Learn how to convert a deep learning model running on notebook environments into production-ready application supporting various deployment environments. Learn conversion between PyTorch and...
Birmingham: Packt Publishing, 2022. — 321 p. — ISBN 180324366X. Supercharge your skills for tailoring deep-learning models and deploying them in production environments with ease and precision. Key Features Learn how to convert a deep learning model running on notebook environments into production-ready application supporting various deployment environments. Learn conversion...
Pack, 2020. - 449p. - ISBN: 9781800200456 Start with the basics of reinforcement learning and explore deep learning concepts such as deep Q-learning, deep recurrent Q-networks, and policy-based methods with this practical guide Key Features Use TensorFlow to write reinforcement learning agents for performing challenging tasks Learn how to solve finite Markov decision problems...
Pack, 2020. - 449p. - ISBN: 9781800200456 Start with the basics of reinforcement learning and explore deep learning concepts such as deep Q-learning, deep recurrent Q-networks, and policy-based methods with this practical guide Key Features Use TensorFlow to write reinforcement learning agents for performing challenging tasks Learn how to solve finite Markov decision problems...
Apress, 2020. — 259 p. — ISBN: 1484251237. Harness the power of MatLAB for deep-learning challenges . This book provides an introduction to deep learning and using MatLAB's deep-learning toolboxes . You’ll see how these toolboxes provide the complete set of functions needed to implement all aspects of deep learning. Along the way, you'll learn to model complex systems,...
2nd Edition. — Apress, 2022. — 338 p. – ISBN-13 978-1-4842-7911-3. Harness the power of MatLAB for deep-learning challenges. Practical MatLAB Deep Learning, Second Edition, remains a one-of a-kind book that provides an introduction to deep learning and using MatLAB's deep-learning toolboxes. In this book, you’ll see how these toolboxes provide the complete set of functions...
2nd Edition. — Apress Media LLC., 2022. — 348 p. – ISBN-13: 978-1-4842-7912-0. Harness the power of MatLAB for deep-learning challenges. Practical MatLAB Deep Learning, Second Edition, remains a one-of a-kind book that provides an introduction to deep learning and using MatLAB's deep-learning toolboxes. In this book, you’ll see how these toolboxes provide the complete set of...
2nd Edition. — Apress Media LLC., 2022. — 348 p. – ISBN-13: 978-1-4842-7912-0. Harness the power of MatLAB for deep-learning challenges. Practical MatLAB Deep Learning, Second Edition, remains a one-of a-kind book that provides an introduction to deep learning and using MatLAB's deep-learning toolboxes. In this book, you’ll see how these toolboxes provide the complete set of...
2nd Edition. — Apress Media LLC., 2022. — 348 p. – ISBN-13: 978-1-4842-7912-0. Harness the power of MatLAB for deep-learning challenges. Practical MatLAB Deep Learning, Second Edition, remains a one-of a-kind book that provides an introduction to deep learning and using MatLAB's deep-learning toolboxes. In this book, you’ll see how these toolboxes provide the complete set of...
Apress, 2021. — 388 p. — ISBN 978-1-4842-7340-1. Use TensorFlow 2.x in the Google Colab ecosystem to create state-of-the-art deep learning models guided by hands-on examples. The Colab ecosystem provides a free cloud service with easy access to on-demand GPU (and TPU) hardware acceleration for fast execution of the models you learn to build. This book teaches you...
BPB Publications, 2021 — 440 p. — ISBN: 9789389898118. Learn how to redesign NLP applications from scratch. Natural language processing (NLP) is one of the areas where many Machine Learning and Deep Learning techniques are applied. This book covers wide areas, including the fundamentals of Machine Learning, Understanding and optimizing Hyperparameters, Convolution Neural...
2nd Edition. — Apress Media, LLC., 2023. — 672 p. — ISBN-13: 978-1-4842-8930-3. This book builds upon the foundations established in its first edition, with updated chapters and the latest code implementations to bring it up to date with Tensorflow 2.0. Pro Deep Learning with TensorFlow 2.0 begins with the mathematical and core technical foundations of deep learning. Next, you...
2nd Edition. — Apress Media, LLC., 2023. — 672 p. — ISBN13: 978-1-4842-8931-0. This book builds upon the foundations established in its first edition, with updated chapters and the latest code implementations to bring it up to date with Tensorflow 2.0. Pro Deep Learning with TensorFlow 2.0 begins with the mathematical and core technical foundations of deep learning. Next, you...
2nd Edition. — Apress Media, LLC., 2023. — 672 p. — ISBN13: 978-1-4842-8931-0. This book builds upon the foundations established in its first edition, with updated chapters and the latest code implementations to bring it up to date with Tensorflow 2.0. Pro Deep Learning with TensorFlow 2.0 begins with the mathematical and core technical foundations of deep learning. Next, you...
2nd Edition. — Apress Media, LLC., 2023. — 672 p. — ISBN13: 978-1-4842-8931-0. This book builds upon the foundations established in its first edition, with updated chapters and the latest code implementations to bring it up to date with Tensorflow 2.0. Pro Deep Learning with TensorFlow 2.0 begins with the mathematical and core technical foundations of deep learning. Next, you...
O’Reilly Media, 2017. — 538 p. — ISBN: 978-1-491-91425-0. True PDF Although interest in machine learning has reached a high point, lofty expectations often scuttle projects before they get very far. How can machine learning—especially deep neural networks—make a real difference in your organization? This hands-on guide not only provides the most practical information available...
O’Reilly Media, 2017. — 538 p. — ASIN B074D5YF1D. Although interest in machine learning has reached a high point, lofty expectations often scuttle projects before they get very far. How can machine learning—especially deep neural networks—make a real difference in your organization? This hands-on guide not only provides the most practical information available on the subject,...
O’Reilly Media, 2017. — 520 p. — ISBN: 978-1-491-91425-0. Looking for one central source where you can learn key findings on machine learning? Deep Learning: A Practitioner's Approach provides developers and data scientists with the most practical information available on the subject, including deep learning theory, best practices, and use cases. Authors Adam Gibson and Josh...
Packt, 2020. — 317 p. — ISBN: 1788996836, 9781788996839. This book starts with a brief overview of machine learning and deep learning and how to build your first neural network. You'll understand the architecture of various deep learning algorithms and their applicable fields, learn how to build deep learning models, optimize hyperparameters, and evaluate model performance....
New York: Springer, 2020. — 347 p. This book introduces readers to the fundamental concepts of deep learning and offers practical insights into how this learning paradigm supports automatic mechanisms of structural knowledge representation. It discusses a number of multilayer architectures giving rise to tangible and functionally meaningful pieces of knowledge, and shows how the...
New York: Springer, 2019. — 296 p. This book offers a timely reflection on the remarkable range of algorithms and applications that have made the area of Deep Learning (DL) so attractive and heavily researched today. Introducing the diversity of learning mechanisms in the environment of Big Data, and presenting authoritative studies in fields such as sensor design, health care,...
BISAC: Computers / Intelligence (AI) & Semantics, 2018. — 394 p. I challenge you to find a field as interesting and exciting as Deep Learning. This book is a spin-off from my previous book "The Deep Learning AI Playbook". The Playbook was meant for a professional audience. This is targeted to a much wider audience. There are two kinds of audiences, those looking to explore and...
Pragmatic Programmers, LLC., 2020. — 342 p. — ISBN: 978-1680506600. You’ve decided to tackle machine learning – because you’re job hunting, embarking on a new project, or just think self-driving cars are cool. But where to start? It’s easy to be intimidated, even as a software developer. The good news is that it doesn’t have to be that hard. Master machine learning by writing...
Pragmatic Programmers, LLC., 2020. — 342 p. — ISBN: 978-1680506600. You’ve decided to tackle machine learning – because you’re job hunting, embarking on a new project, or just think self-driving cars are cool. But where to start? It’s easy to be intimidated, even as a software developer. The good news is that it doesn’t have to be that hard. Master machine learning by writing...
Pragmatic Programmers, LLC., 2020. — 342 p. — ISBN: 978-1680506600. You’ve decided to tackle machine learning – because you’re job hunting, embarking on a new project, or just think self-driving cars are cool. But where to start? It’s easy to be intimidated, even as a software developer. The good news is that it doesn’t have to be that hard. Master machine learning by writing...
Pragmatic Programmers, LLC., 2020. — 342 p. — ISBN: 978-1680506600. You’ve decided to tackle machine learning – because you’re job hunting, embarking on a new project, or just think self-driving cars are cool. But where to start? It’s easy to be intimidated, even as a software developer. The good news is that it doesn’t have to be that hard. Master machine learning by writing...
Pragmatic Programmers, LLC., 2020. — 342 p. — ISBN: 978-1680506600. Code files only! You’ve decided to tackle machine learning – because you’re job hunting, embarking on a new project, or just think self-driving cars are cool. But where to start? It’s easy to be intimidated, even as a software developer. The good news is that it doesn’t have to be that hard. Master machine...
Independently Published, 2024. — 405 p. Unlock the full potential of deep learning with "Deep Learning Deployment with ONNX and CUDA", your comprehensive guide to deploying high-performance AI models across diverse environments. This expertly crafted book navigates the intricate landscape of deep learning deployment, offering in-depth coverage of the pivotal technologies ONNX...
CRC Press, 2024. — 244 p. — eBook ISBN: 978-1-003-29612-6. Natural Language Processing (NLP) is a sub-field of Artificial Intelligence, linguistics, and computer science and is concerned with the generation, recognition, and understanding of human languages, both written and spoken. NLP systems examine the grammatical structure of sentences as well as the specific meanings of...
Academic Press, 2021. — 292 p. — ISBN 978-0-12-822226-3. Trends in Deep Learning Methodologies: Algorithms, Applications, and Systems covers deep learning approaches such as neural networks, deep belief networks, recurrent neural networks, convolutional neural networks, deep auto-encoder, and deep generative networks, which have emerged as powerful computational models....
Springer, 2022. — 421 p. — ISBN 9811906378, 978-9811906374. Deep reinforcement learning has attracted considerable attention recently. Impressive results have been achieved in such diverse fields as autonomous driving, game playing, molecular recombination, and robotics. In all these fields, computer programs have taught themselves to understand problems that were previously...
Springer Singapore, 2022. — 406 p. — ISBN 978-981-19-0638-1. Deep reinforcement learning has attracted considerable attention recently. Impressive results have been achieved in such diverse fields as autonomous driving, game playing, molecular recombination, and robotics. In all these fields, computer programs have taught themselves to understand problems that were previously...
Singapore: Springer, 2022. — 406 p. Deep reinforcement learning has attracted considerable attention recently. Impressive results have been achieved in such diverse fields as autonomous driving, game playing, molecular recombination, and robotics. In all these fields, computer programs have taught themselves to understand problems that were previously considered to be very...
Academic Press/Elsevier, 2023. — 303 p. Diagnostic Biomedical Signal and Image Processing Applications with Deep Learning Methods presents comprehensive research on both medical imaging and medical signals analysis. The book discusses classification, segmentation, detection, tracking and retrieval applications of non-invasive methods such as EEG, ECG, EMG, MRI, fMRI, CT and...
CRC Press, 2023. — 276 р. — ISBN: 978-1-032-34924-4. Object Detection with Deep Learning Models discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and...
New York: Springer, 2021. — 293 p. This book provides a complete illustration of deep learning concepts with case-studies and practical examples useful for real time applications. This book introduces a broad range of topics in deep learning. The authors start with the fundamentals, architectures, tools needed for effective implementation for scientists. They then present...
Springer, 2021. — 293 p. — (EAI/Springer Innovations in Communication and Computing). — ISBN 978-3-030-66518-0. Продвинутое глубокое обучение для инженеров и ученых: практический подход This book provides a complete illustration of deep learning concepts with case-studies and practical examples useful for real time applications. This book introduces a broad range of topics in...
The MIT Press, 2023. — 541 p. An authoritative, accessible, and up-to-date treatment of deep learning that strikes a pragmatic middle ground between theory and practice. Deep Learning is a fast-moving field with sweeping relevance in today’s increasingly digital world. Understanding Deep Learning provides an authoritative, accessible, and up-to-date treatment of the subject,...
The MIT Press, 2023. — 541 p. — ISBN: 978-0-262-04864-4. An authoritative, accessible, and up-to-date treatment of deep learning that strikes a pragmatic middle ground between theory and practice. Deep Learning is a fast-moving field with sweeping relevance in today’s increasingly digital world. Understanding Deep Learning provides an authoritative, accessible, and up-to-date...
The MIT Press, 2023. — 541 p. — ISBN: 978-0-262-04864-4. An authoritative, accessible, and up-to-date treatment of deep learning that strikes a pragmatic middle ground between theory and practice. Deep Learning is a fast-moving field with sweeping relevance in today’s increasingly digital world. Understanding Deep Learning provides an authoritative, accessible, and up-to-date...
The MIT Press, 2023. — 541 p. — ISBN: 978-0-262-04864-4. An authoritative, accessible, and up-to-date treatment of deep learning that strikes a pragmatic middle ground between theory and practice. Deep Learning is a fast-moving field with sweeping relevance in today’s increasingly digital world. Understanding Deep Learning provides an authoritative, accessible, and up-to-date...
Amazon Digital Services LLC, 2019. — 120 р. — ASIN B07GTT616W. Want to learn deep learning and AI, but hate math? This book is an experiment for me. After years of teaching successful deep learning and machine learning courses online, I’ve come to notice a few patterns. One of them is that a large subset of students just RUN AWAY at the sight of math. This is somewhat problematic...
Amazon Digital Services LLC, 2019. — 89 р. — ASIN B07GTT616W. Want to learn deep learning and AI, but hate math? This book is an experiment for me. After years of teaching successful deep learning and machine learning courses online, I’ve come to notice a few patterns. One of them is that a large subset of students just RUN AWAY at the sight of math. This is somewhat problematic...
Amazon Digital Services LLC, 2019. — 89 р. — ASIN B07GTT616W. Want to learn deep learning and AI, but hate math? This book is an experiment for me. After years of teaching successful deep learning and machine learning courses online, I’ve come to notice a few patterns. One of them is that a large subset of students just RUN AWAY at the sight of math. This is somewhat problematic...
Amazon Digital Services LLC, 2019. — 89 р. — ASIN B07GTT616W. Want to learn deep learning and AI, but hate math? This book is an experiment for me. After years of teaching successful deep learning and machine learning courses online, I’ve come to notice a few patterns. One of them is that a large subset of students just RUN AWAY at the sight of math. This is somewhat problematic...
Manning Publications, 2019. — 384 p. — ISBN 9781617295324. Deep Learning and the Game of Go introduces deep learning by teaching you to build a Go-winning bot. As you progress, you’ll apply increasingly complex training techniques and strategies using the Python deep learning library Keras. You’ll enjoy watching your bot master the game of Go, and along the way, you’ll discover...
GitforGits, 2024. — 332 p. — ASIN: B0DM3K9NPC. This is the practical, solution-oriented book for every data scientists, machine learning engineers, and AI engineers to utilize the most of Google JAX for efficient and advanced machine learning. It covers essential tasks, troubleshooting scenarios, and optimization techniques to address common challenges encountered while working...
GitforGits, 2024. — 332 p. — ASIN: B0DM3K9NPC. This is the practical, solution-oriented book for every data scientists, machine learning engineers, and AI engineers to utilize the most of Google JAX for efficient and advanced machine learning. It covers essential tasks, troubleshooting scenarios, and optimization techniques to address common challenges encountered while working...
GitforGits, 2024. — 332 p. — ASIN: B0DM3K9NPC. This is the practical, solution-oriented book for every data scientists, machine learning engineers, and AI engineers to utilize the most of Google JAX for efficient and advanced machine learning. It covers essential tasks, troubleshooting scenarios, and optimization techniques to address common challenges encountered while working...
GitforGits, 2024. — 332 p. — ASIN: B0DM3K9NPC. This is the practical, solution-oriented book for every data scientists, machine learning engineers, and AI engineers to utilize the most of Google JAX for efficient and advanced machine learning. It covers essential tasks, troubleshooting scenarios, and optimization techniques to address common challenges encountered while working...
Manning Publications, 2022. — 602 p. — ISBN 13: 978-1617298639. Written for everyday developers, there are no complex mathematical proofs or unnecessary academic theory in Inside Deep Learning. Journey through the theory and practice of modern deep learning, and apply innovative techniques to solve everyday data problems. Inside Deep Learning is a fast-paced beginner's guide to...
Manning Publications, 2022. — 602 p. — ISBN 13: 978-1617298639. Written for everyday developers, there are no complex mathematical proofs or unnecessary academic theory in Inside Deep Learning. Journey through the theory and practice of modern deep learning, and apply innovative techniques to solve everyday data problems. Inside Deep Learning is a fast-paced beginner's guide to...
Packt Publishing, 2019. — 353 p. — ISBN: 1789538777, 978-1789538779. Discover best practices for choosing, building, training, and improving deep learning models using Keras-R, and TensorFlow-R libraries Key Features Implement deep learning algorithms to build AI models with the help of tips and tricks Understand how deep learning models operate using expert techniques Apply...
Packt Publishing, 2019. — 353 p. — ISBN: 1789538777, 978-1789538779. Discover best practices for choosing, building, training, and improving deep learning models using Keras-R, and TensorFlow-R libraries Key Features Implement deep learning algorithms to build AI models with the help of tips and tricks Understand how deep learning models operate using expert techniques Apply...
Packt Publishing, 2019. — 353 p. — ISBN: 1789538777, 978-1789538779. Discover best practices for choosing, building, training, and improving deep learning models using Keras-R, and TensorFlow-R libraries Key Features Implement deep learning algorithms to build AI models with the help of tips and tricks Understand how deep learning models operate using expert techniques Apply...
Packt Publishing, 2019. — 353 p. — ISBN: 1789538777, 978-1789538779. Discover best practices for choosing, building, training, and improving deep learning models using Keras-R, and TensorFlow-R libraries Key Features Implement deep learning algorithms to build AI models with the help of tips and tricks Understand how deep learning models operate using expert techniques Apply...
Packt Publishing, 2019. — 353 p. — ISBN: 1789538777, 978-1789538779. Discover best practices for choosing, building, training, and improving deep learning models using Keras-R, and TensorFlow-R libraries Key Features Implement deep learning algorithms to build AI models with the help of tips and tricks Understand how deep learning models operate using expert techniques Apply...
Packt Publishing, 2020. — 294 p. — ISBN: 978-1-78899-520-7. Use Java and Deeplearning4j to build robust, enterprise-grade deep learning models from scratch Java is one of the most widely used programming languages in the world. With this book, you’ll see how its popular libraries for deep learning, such as Deeplearning4j (DL4J), make deep learning easy. Starting by configuring...
Packt Publishing, 2020. — 436 p. — ISBN: 978-1-78899-520-7. Use Java and Deeplearning4j to build robust, enterprise-grade deep learning models from scratch Java is one of the most widely used programming languages in the world. With this book, you’ll see how its popular libraries for deep learning, such as Deeplearning4j (DL4J), make deep learning easy. Starting by configuring...
Packt Publishing, 2020. — 436 p. — ISBN: 978-1-78899-520-7. Use Java and Deeplearning4j to build robust, enterprise-grade deep learning models from scratch Java is one of the most widely used programming languages in the world. With this book, you’ll see how its popular libraries for deep learning, such as Deeplearning4j (DL4J), make deep learning easy. Starting by configuring...
Packt Publishing, 2020. — 436 p. — ISBN: 978-1-78899-520-7. Use Java and Deeplearning4j to build robust, enterprise-grade deep learning models from scratch Java is one of the most widely used programming languages in the world. With this book, you’ll see how its popular libraries for deep learning, such as Deeplearning4j (DL4J), make deep learning easy. Starting by configuring...
Packt Publishing, 2020. — 294 p. — ISBN: 978-1-78899-520-7. Code files only! Use Java and Deeplearning4j to build robust, enterprise-grade deep learning models from scratch Java is one of the most widely used programming languages in the world. With this book, you’ll see how its popular libraries for deep learning, such as Deeplearning4j (DL4J), make deep learning easy....
BPB Publications, 2025. — 476 p. — ISBN-13: 978-93-65890-846. Description Explore the world of generative AI, a technology capable of creating new data that closely resembles reality. This book covers the fundamentals and advances through cutting-edge techniques. It also clarifies complex concepts, guiding you through the essentials of deep learning, neural networks, and the...
BPB Publications, 2025. — 476 p. — ISBN-13: 978-93-65890-846. Description Explore the world of generative AI, a technology capable of creating new data that closely resembles reality. This book covers the fundamentals and advances through cutting-edge techniques. It also clarifies complex concepts, guiding you through the essentials of deep learning, neural networks, and the...
BPB Publications, 2025. — 476 p. — ISBN-13: 978-93-65890-846. Description Explore the world of generative AI, a technology capable of creating new data that closely resembles reality. This book covers the fundamentals and advances through cutting-edge techniques. It also clarifies complex concepts, guiding you through the essentials of deep learning, neural networks, and the...
New York: O’Reilly, 2019. — 220 p. Why Deep Learning? Contemporary Life Science Is About Data What Will You Learn? Intro to Deep Learning Linear Models Multilayer Perceptrons Training Models Regularization Hyperparameter Optimization Other Types of Models Further Reading Machine Learning with DeepChem DeepChem Datasets Training a Model to Predict Toxicity of Molecules Case...
O’Reilly, 2019. — 253 p. — ISBN13: 978-1-492-03983-9 Deep learning has already achieved remarkable results in many fields. Now it’s making waves throughout the sciences broadly and the life sciences in particular. This practical book teaches developers and scientists how to use deep learning for genomics, chemistry, biophysics, microscopy, medical analysis, and other fields....
O’Reilly, 2019. — 253 p. — ISBN13: 978-1-492-03983-9 Deep learning has already achieved remarkable results in many fields. Now it’s making waves throughout the sciences broadly and the life sciences in particular. This practical book teaches developers and scientists how to use deep learning for genomics, chemistry, biophysics, microscopy, medical analysis, and other fields....
O’Reilly, 2019. — 253 p. — ISBN13: 978-1-492-03983-9 Deep learning has already achieved remarkable results in many fields. Now it’s making waves throughout the sciences broadly and the life sciences in particular. This practical book teaches developers and scientists how to use deep learning for genomics, chemistry, biophysics, microscopy, medical analysis, and other fields....
Independently published, 2023. — 428 p. "It is like a voyage of discovery, seeking not for new territory but new knowledge. It should appeal to those with a good sense of adventure," Dr. Frederick Sanger. I hope every reader enjoys this voyage in deep learning and find their adventure. Think of deep learning as an art of cooking. One way to cook is to follow a recipe. But when...
Packt Publishing Ltd, 2020. — 332 p. Build autonomous vehicles using deep neural networks and behavior-cloning techniques With self-driving cars (SDCs) being an emerging subject in the field of artificial intelligence, data scientists have now focused their interest on building autonomous cars. This book is a comprehensive guide to using deep learning and computer vision...
Packt Publishing Ltd, 2020. — 332 p. Build autonomous vehicles using deep neural networks and behavior-cloning techniques With self-driving cars (SDCs) being an emerging subject in the field of artificial intelligence, data scientists have now focused their interest on building autonomous cars. This book is a comprehensive guide to using deep learning and computer vision...
Packt Publishing, 2017. — 288 p. Powerful, independent recipes to build deep learning models in different application areas using R libraries About This Book Master intricacies of R deep learning packages such as mxnet & tensorflow Learn application on deep learning in different domains using practical examples from text, image and speech Guide to set-up deep learning models...
Packt Publishing, 2017. — 288 p. — ASIN B071NDMWN2. Powerful, independent recipes to build deep learning models in different application areas using R libraries About This Book Master intricacies of R deep learning packages such as mxnet & tensorflow Learn application on deep learning in different domains using practical examples from text, image and speech Guide to set-up deep...
Packt Publishing, 2017. — 288 p. — ASIN B071NDMWN2. Powerful, independent recipes to build deep learning models in different application areas using R libraries About This Book Master intricacies of R deep learning packages such as mxnet & tensorflow Learn application on deep learning in different domains using practical examples from text, image and speech Guide to set-up deep...
2nd ed. — Packt, 2017. — 501 p. — ISBN: 978-1787125933. Unlock modern machine learning and deep learning techniques with Python by using the latest cutting-edge open source Python libraries. About This Book Second edition of the bestselling book on Machine Learning A practical approach to key frameworks in data science, machine learning, and deep learning Use the most powerful...
2nd ed. — Packt, 2017. — 501 p. — ISBN: 978-1787125933. True PDF Unlock modern machine learning and deep learning techniques with Python by using the latest cutting-edge open source Python libraries. About This Book Second edition of the bestselling book on Machine Learning A practical approach to key frameworks in data science, machine learning, and deep learning Use the most...
Wiley-Scrivener, 2024. — 280 p. Dive into this 15-chapter book on ‘Deep Learning Techniques’ and how its solutions allow computers to learn from experience and understand hierarchy concepts. It provides approaches to deep learning in areas of detection, prediction, and future framework development.
CRC Press, 2023. — 223 p. This book explores how to use generative adversarial networks in a variety of applications and emphasises their substantial advancements over traditional generative models. It concentrates on cutting-edge research in DL and GAN which includes creating new tools and methods for processing text, images, and audio.
2nd Edition. — Packt Publishing, 2020. — 760 p. - ISBN: 9781839210686 Master classic PL, deep RL, distributional RL, inverse RL, and more with OpenAI Gym and TensorFlow With significant enhancement in the quality and quantity of algorithms in recent years, this second edition of Hands-On Reinforcement Learning with Python has been revamped into an example-rich guide to learning...
Packt Publishing, 2019. - 512p. - ISBN: 9781789344158 Understand basic to advanced deep learning algorithms, the mathematical principles behind them, and their practical applications. Key Features Get up-to-speed with building your own neural networks from scratch Gain insights into the mathematical principles behind deep learning algorithms Implement popular deep learning...
Packt Publishing, 2019. - 512p. - ISBN: 9781789344158 Understand basic to advanced deep learning algorithms, the mathematical principles behind them, and their practical applications. Key Features Get up-to-speed with building your own neural networks from scratch Gain insights into the mathematical principles behind deep learning algorithms Implement popular deep learning...
2nd edition. — Packt Publishing, 2020. — 761 p. — ISBN 9781839210686. An example-rich guide for beginners to start their reinforcement and deep reinforcement learning journey with state-of-the-art distinct algorithms Key Features Covers a vast spectrum of basic-to-advanced RL algorithms with mathematical explanations of each algorithm Learn how to implement algorithms with code...
2nd edition. — Packt Publishing, 2020. — 761 p. — ISBN 9781839210686. An example-rich guide for beginners to start their reinforcement and deep reinforcement learning journey with state-of-the-art distinct algorithms Key Features Covers a vast spectrum of basic-to-advanced RL algorithms with mathematical explanations of each algorithm Learn how to implement algorithms with code...
2nd edition. — Packt Publishing, 2020. — 761 p. — ISBN 9781839210686. An example-rich guide for beginners to start their reinforcement and deep reinforcement learning journey with state-of-the-art distinct algorithms Key Features Covers a vast spectrum of basic-to-advanced RL algorithms with mathematical explanations of each algorithm Learn how to implement algorithms with code...
Morgan & Claypool Publisher, 2017. - 124p. - ISBN: 978-1627057288 Machine learning, and specifically deep learning, has been hugely disruptive in many fields of computer science. The success of deep learning techniques in solving notoriously difficult classification and regression problems has resulted in their rapid adoption in solving real-world problems. The emergence of deep...
Morgan & Claypool Publisher, 2017. — 124 p. — ISBN: 978-1627057288. Machine learning, and specifically deep learning, has been hugely disruptive in many fields of computer science. The success of deep learning techniques in solving notoriously difficult classification and regression problems has resulted in their rapid adoption in solving real-world problems. The emergence of deep...
Independently published, 2023. — 131 p. — ASIN B0CQTJ4GNZ. About the technology: Forget predictable pixels and soulless algorithms. GANs, the renegade artists of AI, paint beyond the canvas, blurring reality with their brushstrokes of code. This book is your passport to their rebellion. Short summary: GANs & TensorFlow for Developers is your code-fueled escape hatch from the...
Packt, 2020. — 432 p. — ISBN: 9781838640859. Implementing supervised, unsupervised, and generative deep learning (DL) models using Keras, TensorFlow, and PyTorch Key Features Understand the fundamental machine learning concepts useful in deep learning Learn the underlying mathematical and statistical concepts as you implement smart deep learning models from scratch Explore...
Packt, 2020. — 432 p. — ISBN: 9781838640859. Implementing supervised, unsupervised, and generative deep learning (DL) models using Keras, TensorFlow, and PyTorch Key Features Understand the fundamental machine learning concepts useful in deep learning Learn the underlying mathematical and statistical concepts as you implement smart deep learning models from scratch Explore...
Packt, 2020. — 432 p. — ISBN: 9781838640859. Implementing supervised, unsupervised, and generative deep learning (DL) models using Keras, TensorFlow, and PyTorch Key Features Understand the fundamental machine learning concepts useful in deep learning Learn the underlying mathematical and statistical concepts as you implement smart deep learning models from scratch Explore...
Springer Cham, 2023. — 514 p. — (Studies in Big Data, volume 134) — eBook ISBN: 978-3-031-40688-1. Introduces machine and deep learning approaches for solving challenging problems Collects the latest technological innovations and models related to deep learning Includes representative applications and case studies using cutting-edge technologies In recent years, significant...
Springer Cham, 2023. — 514 p. — (Studies in Big Data, volume 134) — eBook ISBN: 978-3-031-40688-1. Introduces machine and deep learning approaches for solving challenging problems Collects the latest technological innovations and models related to deep learning Includes representative applications and case studies using cutting-edge technologies In recent years, significant...
Cambridge: Cambridge University Press, 2022. — 472 p. — ISBN 1316519333. This textbook establishes a theoretical framework for understanding deep learning models of practical relevance. With an approach that borrows from theoretical physics , Roberts and Yaida provide clear and pedagogical explanations of how realistic deep neural networks actually work. To make results from...
Morgan & Claypool, 2021. - 265p. - ISBN: 1681739682 This book describes deep learning systems: the algorithms, compilers, and processor components to efficiently train and deploy deep learning models for commercial applications. The exponential growth in computational power is slowing at a time when the amount of compute consumed by state-of-the-art deep learning (DL) workloads...
Morgan & Claypool, 2020. — 236 p. — (Synthesis Lectures on Computer Architecture). — ISBN 10 1681739666, 13 978-1681739663. This book describes deep learning systems: the algorithms, compilers, and processor components to efficiently train and deploy deep learning models for commercial applications. The purpose of this book is to provide a solid understanding of (1) the design,...
PyImageSearch, 2017. — 321 p. Welcome to the Practitioner Bundle of Deep Learning for Computer Vision with Python! This volume is meant to be the next logical step in your deep learning for computer vision education after completing the Starter Bundle. At this point, you should have a strong understanding of the fundamentals of parameterized learning, neural networks, and...
MDPI, 2023. — 284 p. This book highlights the importance of Deep Learning (DL), which has garnered significant attention in science, industry, and academia. It draws inspiration from the functioning of the human brain and the concept of learning. Unlike traditional and Machine Learning (ML) methods, Deep Learning techniques emulate the human brain's neural networks at a lower...
Boca Raton: CRC Press, 2024. — 217 p. The book aims to highlight the potential of Deep Learning (DL)-enabled methods in intelligent fault diagnosis (IFD), along with their benefits and contributions. The authors first introduce basic applications of DL-enabled IFD, including auto-encoders, deep belief networks, and convolutional neural networks. Advanced topics of DL-enabled...
Independently published, 2019. — 180 p. — ISBN 1709576030. What if you could teach your computer how to learn the way the human brain does? And what if you could do that even without having any background in programming? If you think that this is something that may have a huge impact on your life please keep reading, because you are right… it is! If you are reading this you...
Independently published, 2019. — 180 p. — ISBN 1709576030. What if you could teach your computer how to learn the way the human brain does? And what if you could do that even without having any background in programming? If you think that this is something that may have a huge impact on your life please keep reading, because you are right… it is! If you are reading this you...
Manning Publications Co., 2025. — 504 p. — ISBN: 978-1633438545. Business runs on tabular data in databases, spreadsheets, and logs. Crunch that data using deep learning, gradient boosting, and other machine learning techniques. Machine Learning for Tabular Data teaches you to train insightful machine learning models on common tabular business data sources such as spreadsheets,...
Manning Publications Co., 2025. — 504 p. — ISBN: 978-1633438545. Business runs on tabular data in databases, spreadsheets, and logs. Crunch that data using deep learning, gradient boosting, and other machine learning techniques. Machine Learning for Tabular Data teaches you to train insightful machine learning models on common tabular business data sources such as spreadsheets,...
Manning Publications Co., 2025. — 504 p. — ISBN: 978-1633438545. Business runs on tabular data in databases, spreadsheets, and logs. Crunch that data using deep learning, gradient boosting, and other machine learning techniques. Machine Learning for Tabular Data teaches you to train insightful machine learning models on common tabular business data sources such as spreadsheets,...
Manning Publications Co., 2025. — 504 p. — ISBN: 978-1633438545. Business runs on tabular data in databases, spreadsheets, and logs. Crunch that data using deep learning, gradient boosting, and other machine learning techniques. Machine Learning for Tabular Data teaches you to train insightful machine learning models on common tabular business data sources such as spreadsheets,...
Manning Publications, 2020. — 266 p. — ISBN 1617296724, 9781617296727. Deep learning offers the potential to identify complex patterns and relationships hidden in data of all sorts. Deep Learning with Structured Data shows you how to apply powerful deep learning analysis techniques to the kind of structured, tabular data you’ll find in the relational databases that real-world...
Manning, 2021. - 264p. - ISBN: 9781617296727 Deep Learning with Structured Data teaches you powerful data analysis techniques for tabular data and relational databases. Deep learning offers the potential to identify complex patterns and relationships hidden in data of all sorts. Deep Learning with Structured Data shows you how to apply powerful deep learning analysis techniques...
Manning Publications, 2020. — 266 p. — ISBN 1617296724, 9781617296727. Deep learning offers the potential to identify complex patterns and relationships hidden in data of all sorts. Deep Learning with Structured Data shows you how to apply powerful deep learning analysis techniques to the kind of structured, tabular data you’ll find in the relational databases that real-world...
Manning Publications Co., 2020. — 241 p. — ISBN: 978-1617296727. Deep learning offers the potential to identify complex patterns and relationships hidden in data of all sorts. Deep Learning with Structured Data shows you how to apply powerful deep learning analysis techniques to the kind of structured, tabular data you'll find in the relational databases that real-world...
Manning Publications Co., 2020. — 241 p. — ISBN: 978-1617296727. Deep learning offers the potential to identify complex patterns and relationships hidden in data of all sorts. Deep Learning with Structured Data shows you how to apply powerful deep learning analysis techniques to the kind of structured, tabular data you'll find in the relational databases that real-world...
Manning Publications Co., 2020. — 241 p. — ISBN: 978-1617296727. Deep learning offers the potential to identify complex patterns and relationships hidden in data of all sorts. Deep Learning with Structured Data shows you how to apply powerful deep learning analysis techniques to the kind of structured, tabular data you'll find in the relational databases that real-world...
Manning Publications Co., 2020. — 241 p. — ISBN: 978-1617296727. Deep learning offers the potential to identify complex patterns and relationships hidden in data of all sorts. Deep Learning with Structured Data shows you how to apply powerful deep learning analysis techniques to the kind of structured, tabular data you'll find in the relational databases that real-world...
Manning Publications, 2020. — 266 p.— ISBN 1617296724, 9781617296727. Deep learning offers the potential to identify complex patterns and relationships hidden in data of all sorts. Deep Learning with Structured Data shows you how to apply powerful deep learning analysis techniques to the kind of structured, tabular data you’ll find in the relational databases that real-world...
IGI Global, 2020. - 405p. - ISBN: 9781799850687 Wireless sensor networks have gained significant attention industrially and academically due to their wide range of uses in various fields. Because of their vast amount of applications, wireless sensor networks are vulnerable to a variety of security attacks. The protection of wireless sensor networks remains a challenge due to...
Packt Publishing, 2021. — 317 p. — ISBN 9781800206137. Discover ways to implement various deep learning algorithms by leveraging Python and other technologies Key Features Learn deep learning models through several activities Begin with simple machine learning problems, and finish by building a complex system of your own Teach your machines to see by mastering the technologies...
Packt Publishing, 2021. — 317 p. — ISBN 9781800206137. Discover ways to implement various deep learning algorithms by leveraging Python and other technologies Key Features Learn deep learning models through several activities Begin with simple machine learning problems, and finish by building a complex system of your own Teach your machines to see by mastering the technologies...
Packt Publishing, 2021. — 317 p. — ISBN 9781800206137. Discover ways to implement various deep learning algorithms by leveraging Python and other technologies Key Features Learn deep learning models through several activities Begin with simple machine learning problems, and finish by building a complex system of your own Teach your machines to see by mastering the technologies...
Packt Publishing, 2021. — 317 p. — ISBN 9781800206137. Code Files Only! Discover ways to implement various deep learning algorithms by leveraging Python and other technologies Key Features Learn deep learning models through several activities Begin with simple machine learning problems, and finish by building a complex system of your own Teach your machines to see by mastering...
Academic Press, 2019. — 269 p. — ISBN: 978-0-12-816718-2. This book delivers a significant forum for the technical advancement of deep learning in parallel computing environment across bio-engineering diversified domains and its applications. Pursuing an interdisciplinary approach, it focuses on methods used to identify and acquire valid, potentially useful knowledge sources....
Apress 2021. — 394 p. — ISBN 978-1484268087. Deep reinforcement learning is a fast-growing discipline that is making a significant impact in fields of autonomous vehicles, robotics, healthcare, finance, and many more. This book covers deep reinforcement learning using deep-q learning and policy gradient models with coding exercise. You'll begin by reviewing the Markov decision...
Apress 2021. — 394 p. — ISBN 978-1484268087. Deep reinforcement learning is a fast-growing discipline that is making a significant impact in fields of autonomous vehicles, robotics, healthcare, finance, and many more. This book covers deep reinforcement learning using deep-q learning and policy gradient models with coding exercise. You'll begin by reviewing the Markov decision...
Apress, 2021. — 394 p. — ISBN 978-1484268087. Deep reinforcement learning is a fast-growing discipline that is making a significant impact in fields of autonomous vehicles, robotics, healthcare, finance, and many more. This book covers deep reinforcement learning using deep-q learning and policy gradient models with coding exercise. You'll begin by reviewing the Markov decision...
Apress, 2021. — 394 p. — ISBN 978-1484268087. Source Code only! Deep reinforcement learning is a fast-growing discipline that is making a significant impact in fields of autonomous vehicles, robotics, healthcare, finance, and many more. This book covers deep reinforcement learning using deep-q learning and policy gradient models with coding exercise. You'll begin by reviewing...
Springer Cham 2021. — 104 p. — ISBN 978-3-030-94482-7. The book represents the first attempt to systematically deal with the use of deep neural networks to forecast chaotic time series. Differently from most of the current literature, it implements a multi-step approach, i.e., the forecast of an entire interval of future values. This is relevant for many applications, such as...
Springer Cham 2021. — 104 p. — ISBN 978-3-030-94482-7. The book represents the first attempt to systematically deal with the use of deep neural networks to forecast chaotic time series. Differently from most of the current literature, it implements a multi-step approach, i.e., the forecast of an entire interval of future values. This is relevant for many applications, such as...
Artech House, 2021. — 361 p. — ISBN 978-1-63081-746-6. This exciting new resource presents emerging applications of artificial intelligence and deep learning in short-range radar. The book covers applications ranging from industrial, consumer space to emerging automotive applications. The book presents several human-machine interface (HMI) applications, such as gesture...
Santra Avik, Hazra Souvik, Servadei Lorenzo, Thomas Stadelmayer, Michael Stephan, Anand Dubey. — Wiley-IEEE Press, 2023. — 332 p. — ISBN 978-1119910657. Introduces multiple state-of-the-art Deep Learning architectures for mmwave radar in a variety of advanced applications. Methods and Techniques in Deep Learning: Advancements in mmWave Radar Solutions provides a timely and...
Wiley-IEEE Press, 2024. — 259 p. Discover how to train Deep Learning models by learning how to build real Deep Learning software libraries and verification software! The study of Deep Learning and Artificial Neural Networks (ANN) is a significant subfield of artificial intelligence (AI) that can be found within numerous fields: medicine, law, financial services, and science,...
Wiley-IEEE Press, 2024. — 259 p. — ISBN: 978-1394205608. Discover how to train Deep Learning models by learning how to build real Deep Learning software libraries and verification software! The study of Deep Learning and Artificial Neural Networks (ANN) is a significant subfield of artificial intelligence (AI) that can be found within numerous fields: medicine, law, financial...
Wiley-IEEE Press, 2024. — 259 p. — ISBN: 978-1394205608. Discover how to train Deep Learning models by learning how to build real Deep Learning software libraries and verification software! The study of Deep Learning and Artificial Neural Networks (ANN) is a significant subfield of artificial intelligence (AI) that can be found within numerous fields: medicine, law, financial...
Wiley-IEEE Press, 2024. — 259 p. — ISBN: 978-1394205608. Discover how to train Deep Learning models by learning how to build real Deep Learning software libraries and verification software! The study of Deep Learning and Artificial Neural Networks (ANN) is a significant subfield of artificial intelligence (AI) that can be found within numerous fields: medicine, law, financial...
Manning Publications, 2024. — 410 p. — (Final). — ISBN 9781633438880. Embark on a journey into the world of JAX, a cutting-edge library that’s rev olutionizing deep learning and high-performance computing. In this opening part of JAX for Deep Learning, we lay the groundwork for understanding why JAX is a pivotal tool in the ever-evolving landscape of machine learning...
Manning Publications, 2024. — 408 p. — ISBN-13: 978-1633438880. Accelerate deep learning and other number-intensive tasks with JAX, Google’s awesome high-performance numerical computing library. The JAX numerical computing library tackles the core performance challenges at the heart of deep learning and other scientific computing tasks. By combining Google’s Accelerated Linear...
Manning Publications, 2024. — 408 p. — ISBN-13: 978-1633438880. Accelerate deep learning and other number-intensive tasks with JAX, Google’s awesome high-performance numerical computing library. The JAX numerical computing library tackles the core performance challenges at the heart of deep learning and other scientific computing tasks. By combining Google’s Accelerated Linear...
Manning Publications, 2024. — 408 p. — ISBN-13: 978-1633438880. Accelerate deep learning and other number-intensive tasks with JAX, Google’s awesome high-performance numerical computing library. The JAX numerical computing library tackles the core performance challenges at the heart of deep learning and other scientific computing tasks. By combining Google’s Accelerated Linear...
Birmingham: Packt Publishing, 2022. — 363 p. — ISBN 180056161X. Build, train, deploy, and scale deep learning models quickly and accurately, improving your productivity using the lightweight PyTorch Wrapper. Key Features Become well-versed with PyTorch Lightning architecture and learn how it can be implemented in various industry domains. Speed up your research using PyTorch...
The MIT Press, 2018. — 352 p. — ISBN13: 978-0-2620-3803-4. How deep learning — from Google Translate to driverless cars to personal cognitive assistants — is changing our lives and transforming every sector of the economy. The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous...
The MIT Press, 2018. — 352 р. How deep learning — from Google Translate to driverless cars to personal cognitive assistants — is changing our lives and transforming every sector of the economy. The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading...
Packt Publishing, 2019. — 314 p. — ISBN: 978-1-78934-099-0. Apply modern deep learning techniques to build and train deep neural networks using Gorgonia Go is an open source programming language designed by Google for handling large-scale projects efficiently. The Go ecosystem comprises some really powerful deep learning tools such as DQN and CUDA. With this book, you’ll be...
Packt Publishing, 2019. — 314 p. — ISBN: 978-1-78934-099-0. Apply modern deep learning techniques to build and train deep neural networks using Gorgonia Go is an open source programming language designed by Google for handling large-scale projects efficiently. The Go ecosystem comprises some really powerful deep learning tools such as DQN and CUDA. With this book, you’ll be...
Packt Publishing, 2019. — 228 p. — ISBN: 978-1-78934-099-0. Code files only! Apply modern deep learning techniques to build and train deep neural networks using Gorgonia Go is an open source programming language designed by Google for handling large-scale projects efficiently. The Go ecosystem comprises some really powerful deep learning tools such as DQN and CUDA. With this...
Packt Publishing, 2019. — 303 p. — ISBN: 978-1-78934-099-0. Key Features Gain a practical understanding of deep learning using Golang Build complex neural network models using Go libraries and Gorgonia Take your deep learning model from design to deployment with this handy guide Book Description Go is an open source programming language designed by Google for handling...
Packt Publishing, 2019. — 303 p. — ISBN: 978-1-78934-099-0. Key Features Gain a practical understanding of deep learning using Golang Build complex neural network models using Go libraries and Gorgonia Take your deep learning model from design to deployment with this handy guide Book Description Go is an open source programming language designed by Google for handling...
Packt, 2019. — 242 p. — ISBN: 1789340993. Apply modern deep learning techniques to build and train deep neural networks using Gorgonia Key Features Gain a practical understanding of deep learning using Golang Build complex neural network models using Go libraries and Gorgonia Take your deep learning model from design to deployment with this handy guide Book Description Go is an...
Packt, 2019. — 242 p. — ISBN: 1789340993. Apply modern deep learning techniques to build and train deep neural networks using Gorgonia Key Features Gain a practical understanding of deep learning using Golang Build complex neural network models using Go libraries and Gorgonia Take your deep learning model from design to deployment with this handy guide Book Description Go is an...
IGI Global, 2020. — 346 p. — ISBN 9781799821090. Deep learning includes a subset of machine learning for processing the unsupervised data with artificial neural network functions. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. When applied to engineering, deep learning can have a great...
Vivek S. Sharma, Shubham Mahajan, Anand Nayyar, Amit Kant Pandit (Editor). — CRC Press, 2025. — 390 p. — ISBN: 978-1032931999. Unlock the transformative potential of deep learning in your professional and academic endeavors with Deep Learning in Engineering, Energy and Finance: Principals and Applications. This comprehensive guide seamlessly bridges the gap between theoretical...
Vivek S. Sharma, Shubham Mahajan, Anand Nayyar, Amit Kant Pandit (Editor). — CRC Press, 2025. — 390 p. — ISBN: 978-1003564874. Unlock the transformative potential of deep learning in your professional and academic endeavors with Deep Learning in Engineering, Energy and Finance: Principals and Applications. This comprehensive guide seamlessly bridges the gap between theoretical...
Vivek S. Sharma, Shubham Mahajan, Anand Nayyar, Amit Kant Pandit (Editor). — CRC Press, 2025. — 390 p. — ISBN: 978-1003564874. Unlock the transformative potential of deep learning in your professional and academic endeavors with Deep Learning in Engineering, Energy and Finance: Principals and Applications. This comprehensive guide seamlessly bridges the gap between theoretical...
Vivek S. Sharma, Shubham Mahajan, Anand Nayyar, Amit Kant Pandit (Editor). — CRC Press, 2025. — 390 p. — ISBN: 978-1003564874. Unlock the transformative potential of deep learning in your professional and academic endeavors with Deep Learning in Engineering, Energy and Finance: Principals and Applications. This comprehensive guide seamlessly bridges the gap between theoretical...
BPB Publications, 2022. — 315 p. This book begins with the configuration of an Anaconda development environment, essential for practicing the deep learning process. The basics of machine learning, which are needed for Deep Learning, are explained in this book. TensorFlow is the industry-standard library for Deep Learning, and thereby, it is covered extensively with both...
Springer Cham, 2023. — 161 p. — (Springer Handbooks) — eBook ISBN: 978-3-031-39244-3. Easy-to-understand description of the multiple facets of design, development and deployment of deep learning networks Practical tools that facilitate understanding of underlying technology Covers wide-ranging conceptual modeling and programming tools that animate deep learning applications...
Springer, 2023. — 172 p. — ISBN 3031392434. This textbook presents multiple facets of design, development and deployment of deep learning networks for both students and industry practitioners . It introduces a deep learning tool set with deep learning concepts interwoven to enhance understanding. It also presents the design and technical aspects of programming along with a...
Palm Bay: CRC Press/Apple Academic Press, 2022. — 289 p. An enlightening amalgamation of deep learning concepts with visual computing and signal processing applications, this new volume covers the fundamentals and advanced topics in designing and deploying techniques using deep architectures and their application in visual computing and signal processing. The volume first lays...
Springer Singapore, 2025. — 610 p. — (Studies in Big Data, volume 162). — eBook ISBN 978-981-97-8019-8. Delves deeper into the mathematical intricacies of tensors in AI. Provides focused exploration of tensor calculus and its applications in deep learning. Includes summaries, illustrative examples, and exercises aimed at reinforcing the reader's understanding of the material....
Springer Singapore, 2025. — 610 p. — (Studies in Big Data, volume 162). — eBook ISBN 978-981-97-8019-8. Delves deeper into the mathematical intricacies of tensors in AI. Provides focused exploration of tensor calculus and its applications in deep learning. Includes summaries, illustrative examples, and exercises aimed at reinforcing the reader's understanding of the material....
New York: Springer, 2020. — 144 p. This stimulating text/reference presents a philosophical exploration of the conceptual foundations of deep learning, presenting enlightening perspectives that encompass such diverse disciplines as computer science, mathematics, logic, psychology, and cognitive science. The text also highlights select topics from the fascinating history of this...
Springer, 2020. — 140 p. — ISBN: 978-3-030-37591-1 (eBook). This stimulating text/reference presents a philosophical exploration of the conceptual foundations of deep learning, presenting enlightening perspectives that encompass such diverse disciplines as computer science, mathematics, logic, psychology, and cognitive science. The text also highlights select topics from the...
Springer, 2020. — 140 p. — ISBN: 978-3-030-37591-1 (eBook). This stimulating text/reference presents a philosophical exploration of the conceptual foundations of deep learning, presenting enlightening perspectives that encompass such diverse disciplines as computer science, mathematics, logic, psychology, and cognitive science. The text also highlights select topics from the...
Springer, 2020. — 140 p. — ISBN: 978-3-030-37591-1 (eBook). This stimulating text/reference presents a philosophical exploration of the conceptual foundations of deep learning, presenting enlightening perspectives that encompass such diverse disciplines as computer science, mathematics, logic, psychology, and cognitive science. The text also highlights select topics from the...
Springer, 2018. — 119 p. — (Undergraduate Topics in Computer Science). — ISBN: 978-3-319-73003-5. This textbook presents a concise, accessible and engaging first introduction to deep learning, offering a wide range of connectionist models which represent the current state-of-the-art. The text explores the most popular algorithms and architectures in a simple and intuitive...
Springer, 2018. — 119 p. — (Undergraduate Topics in Computer Science). — ISBN: 978-3-319-73003-5. This textbook presents a concise, accessible and engaging first introduction to deep learning, offering a wide range of connectionist models which represent the current state-of-the-art. The text explores the most popular algorithms and architectures in a simple and intuitive...
Springer, 2018. — 196 p. — (Undergraduate Topics in Computer Science). — ISBN: 978-3-319-73003-5. This textbook presents a concise, accessible and engaging first introduction to deep learning, offering a wide range of connectionist models which represent the current state-of-the-art. The text explores the most popular algorithms and architectures in a simple and intuitive...
Springer, 2018. — 196 p. — (Undergraduate Topics in Computer Science). — ISBN: 978-3-319-73003-5. This textbook presents a concise, accessible and engaging first introduction to deep learning, offering a wide range of connectionist models which represent the current state-of-the-art. The text explores the most popular algorithms and architectures in a simple and intuitive...
Independently published, 2021. — 390 p. — ISBN 979-8721791499. This book is not only for programmers and IT professionals but also for businesspeople who are looking forward to boosting their average sales and customer experience. This book contains all the relevant topics that you’ll want to know about deep learning neural networks. You will learn some amazing facts about the...
Independently published, 2021. — 390 p. — ISBN 979-8721791499. This book is not only for programmers and IT professionals but also for businesspeople who are looking forward to boosting their average sales and customer experience. This book contains all the relevant topics that you’ll want to know about deep learning neural networks. You will learn some amazing facts about the...
Independently published, 2021. — 390 p. — ISBN 979-8721791499. This book is not only for programmers and IT professionals but also for businesspeople who are looking forward to boosting their average sales and customer experience. This book contains all the relevant topics that you’ll want to know about deep learning neural networks. You will learn some amazing facts about the...
Independently published, 2020. — 182 p.— ISBN B08S1C9KST. Are you interested in taking your deep learning knowledge to the next level? Then this is the book for you! Machine and deep learning are the future, and there’s no getting away from that. So learning it now, and learning how to do it the right way will put you ahead of the crowd. Deep learning is all about understanding...
Independently published, 2020. — 182 p.— ISBN B08S1C9KST. Are you interested in taking your deep learning knowledge to the next level? Then this is the book for you! Machine and deep learning are the future, and there’s no getting away from that. So learning it now, and learning how to do it the right way will put you ahead of the crowd. Deep learning is all about understanding...
Independently published, 2020. — 182 p.— ISBN B08S1C9KST. Are you interested in taking your deep learning knowledge to the next level? Then this is the book for you! Machine and deep learning are the future, and there’s no getting away from that. So learning it now, and learning how to do it the right way will put you ahead of the crowd. Deep learning is all about understanding...
Independently published, 2022. — 297 p. Learn how to fine-tune the current state-of-the-art EffecientNet V2 model to perform image classification on satellite data (EuroSAT) using TensorFlow in Python. Satellite image classification is undoubtedly crucial for many applications in agriculture, environmental monitoring, urban planning, and more. Applications such as crop...
Independently published, 2022. — 297 p. Learn how to fine-tune the current state-of-the-art EffecientNet V2 model to perform image classification on satellite data (EuroSAT) using TensorFlow in Python. Satellite image classification is undoubtedly crucial for many applications in agriculture, environmental monitoring, urban planning, and more. Applications such as crop...
Academic Press, 2021. — 427 p. — ISBN 978-0-12-823519-5. Generative Adversarial Networks (GAN) have started a revolution in Deep Learning, and today GAN is one of the most researched topics in Artificial Intelligence. Generative Adversarial Networks for Image-to-Image Translation provides a comprehensive overview of the GAN (Generative Adversarial Network) concept starting from...
Springer, 2023. — 483 p. This book is a comprehensive curation, exposition and illustrative discussion of recent research tools for interpretability of Deep Learning models, with a focus on neural network architectures. In addition, it includes several case studies from application-oriented articles in the fields of Computer Vision, optics and Machine Learning related topic....
Springer, 2023. — 483 p. This book is a comprehensive curation, exposition and illustrative discussion of recent research tools for interpretability of Deep Learning models, with a focus on neural network architectures. In addition, it includes several case studies from application-oriented articles in the fields of Computer Vision, optics and Machine Learning related topic....
New York: Springer, 2021. — 212 p. This book provides readers with a comprehensive and recent exposition in deep learning and its multidisciplinary applications, with a concentration on advances of deep learning architectures. The book discusses various artificial intelligence (AI) techniques based on deep learning architecture with applications in natural language processing,...
Chapman and Hall/CRC, 2017. — 364 p. — (Machine Learning & Pattern Recognition). — ISBN: 978-1138626782. Introduction to Machine Learning with Applications in Information Security provides a class-tested introduction to a wide variety of machine learning algorithms, reinforced through realistic applications. The book is accessible and doesn’t prove theorems, or otherwise dwell...
New York: amazon.com Services LLC, 2020. — 264 p. This book will help you to understand the realms of Deep Learning from A-Z. In today’s modern world, Deep Learning has taken over the reins of Machine Learning and Artificial Intelligence. We are all familiar with the term “Deep Learning.” But have you ever wondered what it really is? This book will cover all the major features...
Packt Publishing, 2017. — 744 p. — ISBN: 978-1788470315. Build and run intelligent applications by leveraging key Java machine learning libraries Develop a sound strategy to solve predictive modelling problems using the most popular machine learning Java libraries. Explore a broad variety of data processing, machine learning, and natural language processing through diagrams,...
Packt Publishing, 2017. — 744 p. — ISBN: 978-1788470315. +True PDF Build and run intelligent applications by leveraging key Java machine learning libraries. Develop a sound strategy to solve predictive modelling problems using the most popular machine learning Java libraries. Explore a broad variety of data processing, machine learning, and natural language processing through...
Packt Publishing, 2016. — 254 p. — ISBN: 978-1785282195. AI and Deep Learning are transforming the way we understand software, making computers more intelligent than we could even imagine just a decade ago. Deep Learning algorithms are being used across a broad range of industries – as the fundamental driver of AI, being able to tackle Deep Learning is going to a vital and...
CRC Press, 2022. — 217 p. — ISBN 978-1-032-10446-1. Data science revolves around two giants: Big Data analytics and Deep Learning. It is becoming challenging to handle and retrieve useful information due to how fast data is expanding. This book presents the technologies and tools to simplify and streamline the formation of Big Data as well as Deep Learning systems. This book...
Berlin: de Gruyter, 2022. — 214 p. The book series "Smart Computing Applications" provides a platform for researchers, academicians and practitioners to exchange ideas on recent theoretical and applied data science and computing technologies research, with a particular attention to the possible applications of such technologies in the industry, especially in the field of...
De Gruyter, 2022. — 214 p. — ISBN 978-3-11-075061-4. Cognitive computing simulates human thought processes with self-learning algorithms that utilize data mining, pattern recognition, and natural language processing (NLP). The integration of Deep Learning (DL) improves the performance of Cognitive computing systems in many applications, helping in utilizing heterogeneous data...
De Gruyter, 2022. — 214 p. — ISBN 978-3-11-075061-4. Cognitive computing simulates human thought processes with self-learning algorithms that utilize data mining, pattern recognition, and natural language processing (NLP). The integration of Deep Learning (DL) improves the performance of Cognitive computing systems in many applications, helping in utilizing heterogeneous data...
De Gruyter, 2022. — 214 p. — ISBN 978-3-11-075061-4. Cognitive computing simulates human thought processes with self-learning algorithms that utilize data mining, pattern recognition, and natural language processing (NLP). The integration of Deep Learning (DL) improves the performance of Cognitive computing systems in many applications, helping in utilizing heterogeneous data...
Hershey: IGI Global, 2020. — 310 p. The field of healthcare is seeing a rapid expansion of technological advancement within current medical practices. The implementation of technologies including neural networks, multi-model imaging, genetic algorithms, and soft computing are assisting in predicting and identifying diseases, diagnosing cancer, and the examination of cells....
IGI Global, 2023. — 400 p. — ISBN-13: 978-1668480984. Today’s business world is changing with the adoption of the internet of things (IoT). IoT is helping in prominently capturing a tremendous amount of data from multiple sources. Realizing the future and full potential of IoT devices will require an investment in new technologies. The Handbook of Research on Deep Learning...
IGI Global, 2023. — 400 p. — ISBN-13: 978-1668480984. Today’s business world is changing with the adoption of the internet of things (IoT). IoT is helping in prominently capturing a tremendous amount of data from multiple sources. Realizing the future and full potential of IoT devices will require an investment in new technologies. The Handbook of Research on Deep Learning...
IGI Global, 2023. — 400 p. — ISBN-13: 978-1668480984. Today’s business world is changing with the adoption of the internet of things (IoT). IoT is helping in prominently capturing a tremendous amount of data from multiple sources. Realizing the future and full potential of IoT devices will require an investment in new technologies. The Handbook of Research on Deep Learning...
IGI Global, 2023. — 400 p. — ISBN-13: 978-1668480984. Today’s business world is changing with the adoption of the internet of things (IoT). IoT is helping in prominently capturing a tremendous amount of data from multiple sources. Realizing the future and full potential of IoT devices will require an investment in new technologies. The Handbook of Research on Deep Learning...
BPB Publications, 2023. — 878 p. The book presents you with a thorough introduction to AI and Machine learning, starting from the basics and progressing to a comprehensive coverage of Deep Learning with Python. You will be introduced to the intuition of Neural Networks and how to design and train them effectively. Moving on, you will learn how to use Convolutional Neural...
BPB Publications, 2023. — 624 p. — ISBN 978-93-55513-724. A comprehensive guide to Deep Learning for Beginners Key Features Learn how to design your own neural network efficiently. Learn how to build and train Recurrent Neural Networks (RNNs). Understand how encoding and decoding work in Deep Neural Networks. Description Deep Learning has become increasingly important due to...
Manning Publications, 2019. — 327 p. — ISBN: 1617294799. Deep Learning for Search is a practical book about how to use (deep) neural networks to help build effective search engines. This book examines several components of a search engine, providing insights on how they work and guidance on how neural networks can be used in each context. Emphasis is given to practical,...
Manning Publications, 2019. — 327 p. — ISBN: 1617294799. Deep Learning for Search is a practical book about how to use (deep) neural networks to help build effective search engines. This book examines several components of a search engine, providing insights on how they work and guidance on how neural networks can be used in each context. Emphasis is given to practical,...
J. Joshua Thomas, Pinar Karagoz, B. Bazeer Ahamed, Pandian Vasant. — IGI Global, 2020. — 355 p. — ISBN: 978-1799811947 (ebook). Deep Learning Techniques and Optimization Strategies in Big Data Analytics (Advances in Systems Analysis, Software Engineering, and High Performance Computing) “This book examines the application of artificial intelligence in machine learning, data...
J. Joshua Thomas, Pinar Karagoz, B. Bazeer Ahamed, Pandian Vasant. — IGI Global, 2020. — 355 p. — ISBN: 978-1799811947 (ebook). Deep Learning Techniques and Optimization Strategies in Big Data Analytics (Advances in Systems Analysis, Software Engineering, and High Performance Computing) “This book examines the application of artificial intelligence in machine learning, data...
J. Joshua Thomas, Pinar Karagoz, B. Bazeer Ahamed, Pandian Vasant. — IGI Global, 2020. — 355 p. — ISBN: 978-1799811947 (ebook). Deep Learning Techniques and Optimization Strategies in Big Data Analytics (Advances in Systems Analysis, Software Engineering, and High Performance Computing) “This book examines the application of artificial intelligence in machine learning, data...
J. Joshua Thomas, Pinar Karagoz, B. Bazeer Ahamed, Pandian Vasant. — IGI Global, 2020. — 355 p. — ISBN: 978-1799811947 (ebook). Many approaches have sprouted from artificial intelligence (AI) and produced major breakthroughs in the computer science and engineering industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this...
Manning Publications, 2023. - 272 p. - ISBN 163343902X. Guide machine learning projects from design to production with the techniques in this unique project management guide. No ML skills required ! In Managing Machine Learning Projects you’ll learn essential machine learning project management techniques, including: Understanding an ML project’s requirements. Setting up the...
Manning Publications, 2023. — 623 p. — ISBN: 978-1633439023. Guide machine learning projects from design to production with the techniques in this unique project management guide. No ML skills required ! In Managing Machine Learning Projects you’ll learn essential machine learning project management techniques, including: Understanding an ML project’s requirements. Setting up...
Manning Publications, 2023. — 623 p. — ISBN: 978-1633439023. Guide machine learning projects from design to production with the techniques in this unique project management guide. No ML skills required ! In Managing Machine Learning Projects you’ll learn essential machine learning project management techniques, including: Understanding an ML project’s requirements. Setting up...
Manning Publications, 2023. — 623 p. — ISBN: 978-1633439023. Guide machine learning projects from design to production with the techniques in this unique project management guide. No ML skills required ! In Managing Machine Learning Projects you’ll learn essential machine learning project management techniques, including: Understanding an ML project’s requirements. Setting up...
Independently published, 2022. — 287 p. This document contains a practical and comprehensive introduction of everything related to deep learning in the context of physical simulations. As much as possible, all topics come with hands-on code examples in the form of Jupyter notebooks to quickly get started. Beyond standard supervised learning from data, we’ll look at physical...
Nova Science Publishers, 2021. — 222 p. List of Reviewers Application of Deep Learning in Recommendation System Abstract Background and Terminologies Recommendation System Deep Learning Techniques Autoencoder Recurrent Neural Network Convolution Neural Network Restricted Boltzmann Machine Application of Deep Learning in Recommendation System Collaborative Filtering...
New York: Springer, 2022. — 210 p. This textbook tackles the problem of formulating AI systems by combining probabilistic modeling and deep learning. Moreover, it goes beyond typical predictive modeling and brings together supervised learning and unsupervised learning. The resulting paradigm, called deep generative modeling, utilizes the generative perspective on perceiving the...
2nd Edition: Springer, 2024. — 325 p. — ISBN 978-3-031-64086-5. This first comprehensive book on models behind Generative AI has been thoroughly revised to cover all major classes of deep generative models: mixture models, Probabilistic Circuits, Autoregressive Models, Flow-based Models, Latent Variable Models, GANs, Hybrid Models, Score-based Generative Models, Energy-based...
2nd Edition: Springer, 2024. — 325 p. — ISBN 978-3-031-64086-5. This first comprehensive book on models behind Generative AI has been thoroughly revised to cover all major classes of deep generative models: mixture models, Probabilistic Circuits, Autoregressive Models, Flow-based Models, Latent Variable Models, GANs, Hybrid Models, Score-based Generative Models, Energy-based...
2018. — 204 p. Artificial Intelligence is changing our lives, and solutions based on Deep Learning are leading this transformation. Deep Learning is now of major interest to private companies, since it can be applied to many areas of activity. But getting started in this technology is not an easy task. Many enthusiastic professionals in the field of Deep Learning have difficulties...
2018. — 204 p. Artificial Intelligence is changing our lives, and solutions based on Deep Learning are leading this transformation. Deep Learning is now of major interest to private companies, since it can be applied to many areas of activity. But getting started in this technology is not an easy task. Many enthusiastic professionals in the field of Deep Learning have difficulties...
Shelter Island: Manning, 2019. — 311 p. About this Book Welcome to Why you should learn deep learning Why you should read this book What you need to get started Fundamental Concepts What is deep learning? What is machine learning? Supervised machine learning Unsupervised machine learning Parametric vs nonparametric learning Supervised parametric learning Unsupervised parametric...
Manning Publications Co., 2019. — 335 p. — ISBN: 978-1617293702. Artificial Intelligence is one of the most exciting technologies of the century, and Deep Learning is in many ways the 'brain' behind some of the world's smartest Artificial Intelligence systems out there. Loosely based on neuron behavior inside of human brains, these systems are rapidly catching up with the...
Packt, 2020. — 442 p. — ISBN: 9781789613179. Take your quantitative strategies to the next level by exploring nine examples that make use of cutting-edge deep learning technologies, including CNNs, LSTM, GANs, reinforcement learning, and CapsNets Learn Implement quantitative financial models using the various building blocks of a deep neural network Build, train, and optimize...
Packt, 2020. — 442 p. — ISBN: 9781789613179. Take your quantitative strategies to the next level by exploring nine examples that make use of cutting-edge deep learning technologies, including CNNs, LSTM, GANs, reinforcement learning, and CapsNets Learn Implement quantitative financial models using the various building blocks of a deep neural network Build, train, and optimize...
Packt, 2020. — 442 p. — ISBN: 9781789613179. Take your quantitative strategies to the next level by exploring nine examples that make use of cutting-edge deep learning technologies, including CNNs, LSTM, GANs, reinforcement learning, and CapsNets Learn Implement quantitative financial models using the various building blocks of a deep neural network Build, train, and optimize...
Packt Publishing, 2020. — 574 p. — ISBN: 978-1-78961-317-9. Take your quantitative strategies to the next level by exploring nine examples that make use of cutting-edge deep learning technologies, including CNNs, LSTM, GANs, reinforcement learning, and CapsNets Quantitative methods are the vanguard of the investment management industry. With this book, you’ll learn how you can...
John Wiley & Sons, 2023. — 544 p. — ISBN 978-1-119-84502-7. A concise and practical exploration of key topics and applications in data science In Deep Learning: From Big Data to Artificial Intelligence with R, expert researcher Dr. Stéphane Tufféry delivers an insightful discussion of the applications of deep learning and big data that focuses on practical instructions on...
John Wiley & Sons, 2023. — 544 p. — ISBN 978-1-119-84502-7. A concise and practical exploration of key topics and applications in data science In Deep Learning: From Big Data to Artificial Intelligence with R, expert researcher Dr. Stéphane Tufféry delivers an insightful discussion of the applications of deep learning and big data that focuses on practical instructions on...
John Wiley & Sons, 2023. — 544 p. — ISBN 978-1-119-84502-7. A concise and practical exploration of key topics and applications in data science In Deep Learning: From Big Data to Artificial Intelligence with R, expert researcher Dr. Stéphane Tufféry delivers an insightful discussion of the applications of deep learning and big data that focuses on practical instructions on...
John Wiley & Sons, 2023. — 544 p. — ISBN 978-1-119-84502-7. A concise and practical exploration of key topics and applications in data science In Deep Learning: From Big Data to Artificial Intelligence with R, expert researcher Dr. Stéphane Tufféry delivers an insightful discussion of the applications of deep learning and big data that focuses on practical instructions on...
John Wiley & Sons, 2023. — 544 p. — ISBN 978-1-119-84502-7. A concise and practical exploration of key topics and applications in data science In Deep Learning: From Big Data to Artificial Intelligence with R, expert researcher Dr. Stéphane Tufféry delivers an insightful discussion of the applications of deep learning and big data that focuses on practical instructions on...
CRC Press, 2023. — 140 p. — ISBN 9781003091356. Deep learning is an artificially intelligent entity that teaches itself and can be utilized to make predictions. Deep learning mimics the human brain and provides learned solutions addressing many challenging problems in the area of visual computing. From object recognition to image classification for diagnostics, deep learning...
CRC Press, 2022. — 140 p. — ISBN 9781003091356. Deep learning is an artificially intelligent entity that teaches itself and can be utilized to make predictions. Deep learning mimics the human brain and provides learned solutions addressing many challenging problems in the area of visual computing. From object recognition to image classification for diagnostics, deep learning...
Birmingham: Packt Publishing, 2019. — 455 p. — ISBN: 178995617X. Key Features Get to grips with building faster and more robust deep learning architectures. Investigate and train convolutional neural network (CNN) models with GPU-accelerated libraries such as TensorFlow and PyTorch. Apply deep neural networks (DNNs) to computer vision problems, NLP, and GANs. In order to build...
Birmingham - Mumbai: Packt Publishing, 2019. — 386 p. — ISBN: 978-1789348460, 1789348463. 2nd Edition. Learn advanced state-of-the-art deep learning techniques and their applications using popular Python libraries Key Features Build a strong foundation in neural networks and deep learning with Python libraries Explore advanced deep learning techniques and their applications...
Birmingham - Mumbai: Packt Publishing, 2019. — 386 p. — ISBN: 978-1789348460, 1789348463. 2nd Edition. Learn advanced state-of-the-art deep learning techniques and their applications using popular Python libraries Key Features Build a strong foundation in neural networks and deep learning with Python libraries Explore advanced deep learning techniques and their applications...
Birmingham - Mumbai: Packt Publishing, 2019. — 386 p. — ISBN: 978-1789348460, 1789348463. 2nd Edition. Learn advanced state-of-the-art deep learning techniques and their applications using popular Python libraries Key Features Build a strong foundation in neural networks and deep learning with Python libraries Explore advanced deep learning techniques and their applications...
Birmingham - Mumbai: Packt Publishing, 2019. — 386 p. — ISBN: 978-1789348460, 1789348463. 2nd Edition. Learn advanced state-of-the-art deep learning techniques and their applications using popular Python libraries Key Features Build a strong foundation in neural networks and deep learning with Python libraries Explore advanced deep learning techniques and their applications...
Birmingham - Mumbai: Packt Publishing, 2019. — 386 p. — ISBN: 978-1789348460, 1789348463. 2nd Edition. Learn advanced state-of-the-art deep learning techniques and their applications using popular Python libraries Key Features Build a strong foundation in neural networks and deep learning with Python libraries Explore advanced deep learning techniques and their applications...
Birmingham - Mumbai: Packt Publishing, 2019. — 386 p. — ISBN: 978-1789348460, 1789348463. 2nd Edition. Learn advanced state-of-the-art deep learning techniques and their applications using popular Python libraries Key Features Build a strong foundation in neural networks and deep learning with Python libraries Explore advanced deep learning techniques and their applications...
2nd Edition. — Packt Publishing, 2019. — 468 р. — ISBN: 1789348463. With the surge in artificial intelligence in applications catering to both business and consumer needs, deep learning is more important than ever for meeting current and future market demands. With this book, youll explore deep learning, and learn how to put machine learning to use in your projects. This second...
Packt Publishing, 2020. — 702 p. — ISBN: 978-1-78995-617-7. Gain expertise in advanced deep learning domains such as neural networks, meta-learning, graph neural networks, and memory augmented neural networks using the Python ecosystem In order to build robust deep learning systems, you’ll need to understand everything from how neural networks work to training CNN models. In this...
Packt Publishing, 2020. — 702 p. — ISBN: 978-1-78995-617-7. Gain expertise in advanced deep learning domains such as neural networks, meta-learning, graph neural networks, and memory augmented neural networks using the Python ecosystem In order to build robust deep learning systems, you’ll need to understand everything from how neural networks work to training CNN models. In this...
Packt Publishing, 2020. — 702 p. — ISBN: 978-1-78995-617-7. Gain expertise in advanced deep learning domains such as neural networks, meta-learning, graph neural networks, and memory augmented neural networks using the Python ecosystem In order to build robust deep learning systems, you’ll need to understand everything from how neural networks work to training CNN models. In this...
Packt Publishing, 2020. — 455 p. — ISBN: 978-1-78995-617-7. Code files only! Gain expertise in advanced deep learning domains such as neural networks, meta-learning, graph neural networks, and memory augmented neural networks using the Python ecosystem In order to build robust deep learning systems, you’ll need to understand everything from how neural networks work to training CNN...
Boca Raton: CRC Press, 2022 — 307 p. Deep Learning: A Comprehensive Guide provides comprehensive coverage of Deep Learning and Machine Learning concepts. Deep Learning and Machine Learning are the most sought-after domains, require a deep understanding and this book gives no less than that. This book enables the reader to build innovative and useful applications based on ML and...
CRC Press, 2022. — 307 p. — ISBN 1032028823. Deep Learning: A Comprehensive Guide provides comprehensive coverage of Deep Learning and Machine Learning concepts. Deep Learning and Machine Learning are the most sought-after domains, require a deep understanding and this book gives no less than that. This book enables the reader to build innovative and useful applications based...
Bentham Books, 2023. — 270 р. — ISBN: 978-981-5079-23-4. This book is a detailed reference guide on Deep Learning and its applications. It aims to provide a basic understanding of Deep Learning and its different architectures that are applied to process images, speech, and natural language. It explains basic concepts and many modern use cases through fifteen chapters...
Bentham Books, 2023. — 270 р. — ISBN: 978-981-5079-22-7. This book is a detailed reference guide on Deep Learning and its applications. It aims to provide a basic understanding of Deep Learning and its different architectures that are applied to process images, speech, and natural language. It explains basic concepts and many modern use cases through fifteen chapters...
Bentham Books, 2023. — 270 р. — ISBN: 978-981-5079-22-7. This book is a detailed reference guide on Deep Learning and its applications. It aims to provide a basic understanding of Deep Learning and its different architectures that are applied to process images, speech, and natural language. It explains basic concepts and many modern use cases through fifteen chapters...
Bentham Books, 2023. — 270 р. — ISBN: 978-981-5079-22-7. This book is a detailed reference guide on Deep Learning and its applications. It aims to provide a basic understanding of Deep Learning and its different architectures that are applied to process images, speech, and natural language. It explains basic concepts and many modern use cases through fifteen chapters...
Amazon Digital Services LLC, 2019. — 106 р. Artificial intelligence takes many shapes and forms. At this point in its evolution, machine learning and deep learning are two of the most common shapes it takes. This is primarily because we are at a point where we have discovered how to create networks of information that can actually be filtered and processed just as a normal human...
Manning Publications Co., 2023. — 362 p. — ISBN: 978-1633439863. A vital guide to building the platforms and systems that bring deep learning models to production. In Designing Deep Learning Systems you will learn how to: Transfer your software development skills to deep learning systems Recognize and solve common engineering challenges for deep learning systems Understand the...
Manning Publications Co., 2023. — 362 p. — ISBN: 978-1633439863. A vital guide to building the platforms and systems that bring deep learning models to production. In Designing Deep Learning Systems you will learn how to: Transfer your software development skills to deep learning systems Recognize and solve common engineering challenges for deep learning systems Understand the...
Manning Publications Co., 2023. — 362 p. — ISBN: 978-1633439863. A vital guide to building the platforms and systems that bring deep learning models to production. In Designing Deep Learning Systems you will learn how to: Transfer your software development skills to deep learning systems Recognize and solve common engineering challenges for deep learning systems Understand the...
Manning Publications Co., 2023. — 362 p. — ISBN: 978-1633439863. A vital guide to building the platforms and systems that bring deep learning models to production. In Designing Deep Learning Systems you will learn how to: Transfer your software development skills to deep learning systems Recognize and solve common engineering challenges for deep learning systems Understand the...
Birmingham: Packt Publishing, 2022. — 283 p. — ISBN 1801815690. Build and deploy an efficient data processing pipeline for machine learning model training in an elastic, in-parallel model training or multi-tenant cluster and cloud. Key Features Accelerate model training and interference with order-of-magnitude time reduction. Learn state-of-the-art parallel schemes for both...
Academic Press, 2019. — 283 p. — (Computer Vision and Pattern Recognition). — ISBN 978-0-12-813659-1. Deep Learning through Sparse Representation and Low-Rank Modeling bridges classical sparse and low rank models--those that emphasize problem-specific Interpretability--with recent deep network models that have enabled a larger learning capacity and better utilization of Big...
Academic Press, 2019. — 238 p. — (Computer Vision and Pattern Recognition). — ISBN: 978-0-12-813659-1. This book bridges classical sparse and low rank models—those that emphasize problem-specific Interpretability—with recent deep network models that have enabled a larger learning capacity and better utilization of Big Data. It shows how the toolkit of deep learning is closely...
Bentham Science Publishers, 2023. — 225 p. — eBook ISBN: 978-981-5136-98-2. Numerical Machine Learning is a simple textbook on machine learning that bridges the gap between mathematics theory and practice. The book uses numerical examples with small datasets and simple Python codes to provide a complete walkthrough of the underlying mathematical steps of seven commonly used...
Bentham Science Publishers, 2023. — 225 p. — eBook ISBN: 978-981-5136-98-2. Numerical Machine Learning is a simple textbook on machine learning that bridges the gap between mathematics theory and practice. The book uses numerical examples with small datasets and simple Python codes to provide a complete walkthrough of the underlying mathematical steps of seven commonly used...
Springer, 2021. — 314 p. — ISBN: 9811567581. This book presents selected papers from the 18th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2019). It focuses on deep learning networks and their application in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial...
Springer, 2021. — 314 p. — ISBN: 9811567581. This book presents selected papers from the 18th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2019). It focuses on deep learning networks and their application in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial...
Springer, 2020. — 159 p. — (Studies in Big Data 57). — ISBN: 978-981-13-6793-9. This book introduces readers to both basic and advanced concepts in deep network models. It covers state-of-the-art deep architectures that many researchers are currently using to overcome the limitations of the traditional artificial neural networks. Various deep architecture models and their...
Springer, 2020. — 159 p. — (Studies in Big Data 57). — ISBN: 978-981-13-6793-9. This book introduces readers to both basic and advanced concepts in deep network models. It covers state-of-the-art deep architectures that many researchers are currently using to overcome the limitations of the traditional artificial neural networks. Various deep architecture models and their...
Packt Publishing, 2018. — 284 p. Deep Learning a trending topic in the field of Artificial Intelligence today and can be considered to be an advanced form of machine learning, which is quite tricky to master. This book will help you take your first steps in training efficient deep learning models and applying them in various practical scenarios. You will model, train, and deploy...
Packt Publishing, 2018. — 284 p. Deep Learning a trending topic in the field of Artificial Intelligence today and can be considered to be an advanced form of machine learning, which is quite tricky to master. This book will help you take your first steps in training efficient deep learning models and applying them in various practical scenarios. You will model, train, and deploy...
Packt Publishing, 2018. — 284 p. Deep Learning a trending topic in the field of Artificial Intelligence today and can be considered to be an advanced form of machine learning, which is quite tricky to master. This book will help you take your first steps in training efficient deep learning models and applying them in various practical scenarios. You will model, train, and deploy...
Springer, 2025. — 330 p. As an efficient 3D vision solution, point clouds have been widely applied into diverse engineering scenarios, including immersive media communication, autonomous driving, reverse engineering, robots, topography mapping, digital twin city, medical analysis, digital museum, etc. Thanks to the great developments of Deep Learning theories and methods, 3D...
World Scientific Publishing, 2021. — 641 p. — ISBN 9811234051. This unique compendium discusses some core ideas for the development and implementation of machine learning from three different perspectives — the statistical perspective, the artificial neural network perspective and the deep learning methodology.The useful reference text represents a solid foundation in machine...
World Scientific Publishing, 2021. — 641 p. — ISBN 9811234051. This unique compendium discusses some core ideas for the development and implementation of machine learning from three different perspectives — the statistical perspective, the artificial neural network perspective and the deep learning methodology.The useful reference text represents a solid foundation in machine...
Packt Publishing, 2016. — 170 p. — ISBN: 978-1-78528-058-0. Build automatic classification and prediction models using unsupervised learning. Deep learning is a branch of machine learning based on a set of algorithms that attempt to model high-level abstractions in data by using model architectures. With the superb memory management and the full integration with multi-node big...
Packt Publishing, 2016. — 170 p. — ISBN: 978-1-78528-058-0. Build automatic classification and prediction models using unsupervised learning. Deep learning is a branch of machine learning based on a set of algorithms that attempt to model high-level abstractions in data by using model architectures. With the superb memory management and the full integration with multi-node big...
Packt Publishing, 2016. — 170 p. — ISBN: 978-1-78528-058-0. Build automatic classification and prediction models using unsupervised learning. Deep learning is a branch of machine learning based on a set of algorithms that attempt to model high-level abstractions in data by using model architectures. With the superb memory management and the full integration with multi-node big...
Packt Publishing, 2016. — 170 p. + Code. — ISBN: 978-1-78528-058-0. Build automatic classification and prediction models using unsupervised learning. Deep learning is a branch of machine learning based on a set of algorithms that attempt to model high-level abstractions in data by using model architectures. With the superb memory management and the full integration with...
New York: amazon.com Services LLC, 2020. — 181 p. This book discusses the intricacies of the internal workings of a deep learning model. It addresses the techniques and methods that can not only boost the productivity of your machine learning architectural skills, but also introduces new concepts. Implemented correctly, these can set your deep learning modela league apart from...
GitforGits, 2023. — 118 p. — ISBN-13: 978-8196288358. “Google JAX Essentials” is a comprehensive guide designed for machine learning and deep learning professionals aiming to leverage the power and capabilities of Google’s JAX library in their projects. Over the course of eight chapters, this book takes the reader from understanding the challenges of deep learning and numerical...
GitforGits, 2023. — 118 p. — ISBN-13: 978-8196288358. “Google JAX Essentials” is a comprehensive guide designed for machine learning and deep learning professionals aiming to leverage the power and capabilities of Google’s JAX library in their projects. Over the course of eight chapters, this book takes the reader from understanding the challenges of deep learning and numerical...
GitforGits, 2023. — 118 p. — ISBN-13: 978-8196288358. “Google JAX Essentials” is a comprehensive guide designed for machine learning and deep learning professionals aiming to leverage the power and capabilities of Google’s JAX library in their projects. Over the course of eight chapters, this book takes the reader from understanding the challenges of deep learning and numerical...
GitforGits, 2023. — 118 p. — ISBN-13: 978-8196288358. “Google JAX Essentials” is a comprehensive guide designed for machine learning and deep learning professionals aiming to leverage the power and capabilities of Google’s JAX library in their projects. Over the course of eight chapters, this book takes the reader from understanding the challenges of deep learning and numerical...
Springer, 2024. — 194 p. — (Wireless Networks). — ISBN 978-3-031-57678-2. This book presents Deep Learning techniques for video understanding. For Deep Learning basics, the authors cover Machine Learning pipelines and notations, 2D and 3D Convolutional Neural Networks for spatial and temporal feature learning. For action recognition, the authors introduce classical frameworks...
Springer, 2024. — 194 p. — (Wireless Networks). — ISBN 978-3-031-57678-2. This book presents Deep Learning techniques for video understanding. For Deep Learning basics, the authors cover Machine Learning pipelines and notations, 2D and 3D Convolutional Neural Networks for spatial and temporal feature learning. For action recognition, the authors introduce classical frameworks...
New York: Springer, 2022. — 103 p. The volume of data being collected in solar astronomy has exponentially increased over the past decade and we will be entering the age of petabyte solar data. Deep learning has been an invaluable tool exploited to efficiently extract key information from the massive solar observation data, to solve the tasks of data archiving/classification,...
World Scientific Publishing, 2023. — 309 p. — ISBN 9789811266928. Deep learning, first introduced by Hinton et al. in 2006,1 has brought great changes to the world. Modern deep learning technique relies upon deep neuron networks (DNN), which have a very long history and aim to mimic the functionality of human brains. After more than 15 years of development, it has become a...
Springer, 2023. — 408 p. This book is intended for students, engineers, and researchers interested in both computational mechanics and Deep Learning. It presents the mathematical and computational foundations of Deep Learning (DL) with detailed mathematical formulas in an easy-to-understand manner. It also discusses various applications of Deep Learning in Computational...
Apress Media LLC., 2021. — 630 p. — e-ISBN: 978-1-4842-6513-0. Implement deep learning applications using TensorFlow while learning the “why” through in-depth conceptual explanations. You’ll start by learning what deep learning offers over other machine learning models. Then familiarize yourself with several technologies used to create deep learning models. While some of these...
Apress Media LLC., 2021. — 630 p. — e-ISBN: 978-1-4842-6513-0. Implement deep learning applications using TensorFlow while learning the “why” through in-depth conceptual explanations. You’ll start by learning what deep learning offers over other machine learning models. Then familiarize yourself with several technologies used to create deep learning models. While some of these...
Springer, 2021. — 141 p. — (Texts in Computer Science). — ISBN 978-3-030-61080-7. Integrating concepts from deep learning, machine learning, and artificial neural networks, this highly unique textbook presents content progressively from easy to more complex, orienting its content about knowledge transfer from the viewpoint of machine intelligence. It adopts the methodology from...
2nd. ed. - Springer, 2023. - 234 p. - (Texts in Computer Science). - ISBN 9819948223. The first edition of this textbook was published in 2021 . Over the past two years, we have invested in enhancing all aspects of deep learning methods to ensure the book is comprehensive and impeccable. Taking into account feedback from our readers and audience, the author has diligently...
2nd Edition. — Springer, 2023. — 222 p. — (Texts in Computer Science). — eBook ISBN: 978-981-99-4823-9. The first edition of this textbook was published in 2021. Over the past two years, we have invested in enhancing all aspects of deep learning methods to ensure the book is comprehensive and impeccable. Taking into account feedback from our readers and audience, the author has...
ITexLi, 2023. — 110 p. — ISBN 1803569514 9781803569512 1803569506 9781803569505 1803569522 9781803569529. Deep learning and reinforcement learning are some of the most important and exciting research fields today. With the emergence of new network structures and algorithms such as convolutional neural networks, recurrent neural networks, and self-attention models, these...
Cambridge: Cambridge University Press, 2021. — 339 p. Deep learning on graphs has become one of the hottest topics in machine learning. The book consists of four parts to best accommodate our readers with diverse backgrounds and purposes of reading. Part 1 introduces basic concepts of graphs and deep learning; Part 2 discusses the most established methods from the basic to...
Apress, 2021. — 463 p. — ISBN 1484274121 Learn how to harness modern deep-learning methods in many contexts. Packed with intuitive theory, practical implementation methods, and deep-learning case studies, this book reveals how to acquire the tools you need to design and implement like a deep-learning architect. It covers tools deep learning engineers can use in a wide range of...
Apress Media, LLC., 2023. — 870 p. — ISBN-13: 978-1-4842-8691-3. Deep learning is one of the most powerful tools in the modern Artificial Intelligence landscape. While having been predominantly applied to highly specialized image, text, and signal datasets, this book synthesizes and presents novel deep learning approaches to a seemingly unlikely domain – tabular data. Whether...
Apress Media LLC, 2022. — 463 p. — ISBN-13: 978-1-4842-7412-5. Learn how to harness modern deep-learning methods in many contexts. Packed with intuitive theory, practical implementation methods, and deep-learning case studies, this book reveals how to acquire the tools you need to design and implement like a deep-learning architect. It covers tools deep learning engineers can...
New York: Springer, 2022. — 338 p. The focus of this book is on providing students with insights into geometry that can help them understand deep learning from a unified perspective. Rather than describing deep learning as an implementation technique, as is usually the case in many existing deep learning books, here, deep learning is explained as an ultimate form of signal...
2019. — 536 p. Artificial Intelligence (AI) especially Deep Learning (DL) has made tremendous progress in recent years. It start to spread in many areas, such as: image classification, voice recognition, text generation, language translation etc. As time goes by, it becomes apparent that deep learning will stay in the mainstream. As a technology people, it is time to keep...
2019. — 536 p. Artificial Intelligence (AI) especially Deep Learning (DL) has made tremendous progress in recent years. It start to spread in many areas, such as: image classification, voice recognition, text generation, language translation etc. As time goes by, it becomes apparent that deep learning will stay in the mainstream. As a technology people, it is time to keep...
Manning Publications, 2020. — 384 p. — ISBN: 9781617295430 Deep Reinforcement Learning in Action teaches you how to program agents that learn and improve based on direct feedback from their environment. You’ll build networks with the popular PyTorch deep learning framework to explore reinforcement learning algorithms ranging from Deep Q-Networks to Policy Gradients methods to...
Manning Publications, 2020. — 384 p. — ISBN: 9781617295430 !Code files only Deep Reinforcement Learning in Action teaches you how to program agents that learn and improve based on direct feedback from their environment. You’ll build networks with the popular PyTorch deep learning framework to explore reinforcement learning algorithms ranging from Deep Q-Networks to Policy...
Manning Publications, 2020. — 384 p. — ISBN: 9781617295430. Humans learn best from feedback—we are encouraged to take actions that lead to positive results while deterred by decisions with negative consequences. This reinforcement process can be applied to computer programs allowing them to solve more complex problems that classical programming cannot. Deep Reinforcement...
Manning Publications, 2020. — 384 p. — ISBN: 9781617295430. Humans learn best from feedback—we are encouraged to take actions that lead to positive results while deterred by decisions with negative consequences. This reinforcement process can be applied to computer programs allowing them to solve more complex problems that classical programming cannot. Deep Reinforcement...
Manning Publications, 2020. — 384 p. — ISBN: 9781617295430. Humans learn best from feedback—we are encouraged to take actions that lead to positive results while deterred by decisions with negative consequences. This reinforcement process can be applied to computer programs allowing them to solve more complex problems that classical programming cannot. Deep Reinforcement...
New York: Springer, 2020. — 117 p. — ISBN: 3030343758. This book provides the reader with the fundamental knowledge in the area of Deep Learning (DL) with application to visual content mining. The authors give a fresh view on Deep Learning approaches both from the point of view of image understanding and supervised Machine Learning (ML). It contains chapters which introduce...
New York: Springer, 2020. — 117 p. This book provides the reader with the fundamental knowledge in the area of Deep Learning (DL) with application to visual content mining. The authors give a fresh view on Deep Learning approaches both from the point of view of image understanding and supervised Machine Learning (ML). It contains chapters which introduce theoretical and...
Springer, 2020. — 169 p. — ISBN: 978-3-030-34376-7 (eBook). This book provides the reader with the fundamental knowledge in the area of deep learning with application to visual content mining. The authors give a fresh view on Deep learning approaches both from the point of view of image understanding and supervised machine learning. It contains chapters which introduce...
Springer, 2020. — 169 p. — ISBN: 978-3-030-34376-7 (eBook). This book provides the reader with the fundamental knowledge in the area of deep learning with application to visual content mining. The authors give a fresh view on Deep learning approaches both from the point of view of image understanding and supervised machine learning. It contains chapters which introduce...
GitHub, 2019. — 660 p. Just a few years ago, there were no legions of deep learning scientists developing intelligent products and services at major companies and startups. Machine learning was a forward-looking academic discipline with a narrow set of real-world applications. And those applications, e.g. speech recognition and computer vision, required so much domain knowledge...
Independently published, 2021. — 1029 p. Release 0.16.6, Jun 25, 2021 This book represents our attempt to make deep learning approachable, teaching you the concepts, the context, and the code. Just a few years ago, there were no legions of deep learning scientists developing intelligent products and services at major companies and startups. When we entered the field, machine...
CRC Press, 2023. — 107 p. Computer vision-based crack-like object detection has many useful applications, such as inspecting/monitoring pavement surface, underground pipeline, bridge cracks, railway tracks etc. However, in most contexts, cracks appear as thin, irregular long-narrow objects, and often are buried in complex, textured background with high diversity which make the...
New York: Nova Science Publishers, Inc., 2018. — 398 p. How to utilize digital technology to engage learners in Deep Learning is an issue that warrants significant attention in 21st century education. Deep learning refers to learners' engagement in critical and creative thinking, making inferences and transferring knowledge. Modern technologies like virtual reality, artificial...
Springer Cham, 2023. — 661 p. — eBook ISBN: 978-3-031-29555-3. This book discusses Artificial Neural Networks (ANN) and their ability to predict outcomes using deep and shallow learning principles. The author first describes ANN implementation, consisting of at least three layers that must be established together with cells, one of which is input, the other is output, and the...
Пер. с англ. — СПб.: Диалектика, 2020. — 752 с.: ил. — ISBN: 978-5-907203-01-3. В книге рассматриваются как классические, так и современные модели глубокого обучения. В первых двух главах основной упор сделан на понимании взаимосвязи традиционного машинного обучения и нейронных сетей. Главы 3 и 4 посвящены подробному обсуждению процессов тренировки и регуляризации нейронных...
Пер. с англ. канд. хим. наук А.Г Гузикевича. — СПб.: Диалектика, 2020. — 752 с. — ISBN 978-5-907203-01-3. В книге рассматриваются как классические, так и современные модели глубокого обучения. В первых двух главах основной упор сделан на понимании взаимосвязи традиционного машинного обучения и нейронных сетей. Главы 3 и 4 посвящены подробному обсуждению процессов тренировки и...
М.: Манн, Иванов и Фербер, 2019. — 304 c. Глубокое обучение - машинное обучение, которое строится на идее обучения через примеры. Эта книга разбирает основные идеи этой сложной отрасли изучения искусственного интеллекта. Авторы ставят цель сформировать целостное представление о том, как решаются задачи в области глубокого обучения, какие понятия используются в этой среде и как...
Выходные данные не указаны. 137 с. Схематичное изложение глубокого обучения, применяемого к искусственному интеллекту. Последние хиты глубокого обучения Нейронные сети и глубокое обучение Вдохновление мозгом: как глубокие нейросети произвели революцию в области искусственного интеллекта Глубокое обучение для обработки естественного языка Применение методов Deep Learning к...
Выходные данные не указаны. 139 с. Схематичное изложение применения глубокого обучения для решения задач обработки естественного языка. Последние хиты глубокого обучения Нейронные сети и глубокое обучение Вдохновление мозгом: как глубокие нейросети произвели революцию в области искусственного интеллекта Глубокое обучение для обработки естественного языка Применение методов Deep...
Перев. с англ. И. Рузмайкина, А. Павлов. — СПб.: Питер, 2021. — 272 с.: ил. — (Бестселлеры O’Reilly). — ISBN 978-5-4461-1675-1. Взрывной интерес к нейронным сетям и искусственному интеллекту затронул уже все области жизни, и понимание принципов глубокого обучения необходимо каждому разработчику ПО для решения прикладных задач. Эта практическая книга представляет собой вводный...
Пер. с англ. И. Рузмайкина, А. Павлов. — СПб.: Питер, 2021. — 272 с.: ил. — (Бестселлеры O’Reilly). — ISBN 978-5-4461-1675-1. Если вы уже пытались узнать что-то о нейронных сетях и глубоком обучении, то, скорее всего, столкнулись с изобилием ресурсов, от блогов до массовых открытых онлайн-курсов различного качества и даже книг. Ресурсы по нейронным сетям обычно делятся на две...
М.: ДМК Пресс, 2019. — 585 с. Если вы интересуетесь машинным обучением (Machine Learning) и глубоким обучением (Deep Learning), то этот двухтомник для вас. Эта книга не похожа на большинство других учебников и руководств по глубокому обучению - в ней нет ни детального алгоритмического анализа, сопровождаемого обширной математикой, ни развернутых листингов программного кода....
М.: ДМК Пресс, 2020. — 611 с. Если вы интересуетесь машинным обучением (Machine Learning) и глубоким обучением (Deep Learning), то этот двухтомник для вас. Эта книга не похожа на большинство других учебников и руководств по глубокому обучению - в ней нет ни детального алгоритмического анализа, сопровождаемого обширной математикой, ни развернутых листингов программного кода....
СПб.: Питер, 2022. — 416 с. — (Библиотека программиста). Глубокое обучение с подкреплением (глубокое RL) сочетает в себе два подхода к машинному обучению. В ходе такого обучения виртуальные агенты учатся решать последовательные задачи о принятии решений. За последнее десятилетие было много неординарных достижений в этой области — от однопользовательских и многопользовательских...
Пер. с англ. К. Синица. — СПб.: Питер, 2022. — 416 с. — (Библиотека программиста). — ISBN 978-5-4461-1699-7. Глубокое обучение с подкреплением (глубокое RL) сочетает в себе два подхода к машинному обучению. В ходе такого обучения виртуальные агенты учатся решать последовательные задачи о принятии решений. За последнее десятилетие было много неординарных достижений в этой...
М.: ДМК Пресс, 2018. — 653 с. — ISBN: 9785970606186. Глубокое обучение — это вид машинного обучения, наделяющий компьютеры способностью учиться на опыте и понимать мир в терминах иерархии концепций. Поскольку компьютер приобретает знания из опыта, отпадает нужда в человеке-операторе, который формально описывает необходимые компьютеру знания. Иерархическая организация позволяет...
Учебное пособие. — Тамбов: Тамбовский государственный технический университет, 2023. — 160 с. — ISBN 978-5-8265-2659-0. Представляет собой комплексное руководство, предназначенное для изучения и применения фреймворков PyTorch и PyTorch Lightning в контексте задач глубокого обучения с акцентом на область компьютерного зрения. Предназначено для студентов 3 и 4 курсов направления...
Учебное пособие. — Тамбов: Тамбовский государственный технический университет (ТГТУ), 2023. — 160 с. — ISBN 978-5-8265-2659-0. Представляет собой комплексное руководство, предназначенное для изучения и применения фреймворков PyTorch и PyTorch Lightning в контексте задач глубокого обучения с акцентом на область компьютерного зрения. Предназначено для студентов 3 и 4 курсов...
М.: Эксмо, 2022. —160 с. — (Библиотека MIT) ISBN: 978-5-04-116355-6 Глубокое обучение открывает дорогу инновациям и изменениям во всех сферах современной жизни. Большинство прорывов в области искусственного интеллекта, о которых вы знаете из новостей, основаны на глубоком обучении. Понимание этого предмета полезно как предпринимателям, внедряющим данную технологию в своем...
М.: Бином, 2022. — 162 с. В этой книге простым и доступным для неспециалистов языком раскрываются такие сложные темы, как искусственный интеллект, нейросети, машинное обучение, глубокое обучение. Автор рассказывает о предпосылках глубокого обучения, его истории и базовых основах, а также проводит экскурс в будущее этой технологии, раскрывая перед читателями ее потенциал.
СПб.: Питер, 2020. — 400 с. — (Библиотека программиста) — ISBN 9780135116692, 0135116694. Глубокое обучение стало мощным двигателем для работы с искусственным интеллектом. Яркие иллюстрации и простые примеры кода избавят вас от необходимости вникать в сложные аспекты конструирования моделей глубокого обучения, делая сложные задачи доступными и увлекательными... Джон Крон, Грант...
СПб.: Питер, 2020. — 400 стр. — (Библиотека программиста) — ISBN 9785446115747, 9780135116692, 0135116694. Глубокое обучение стало мощным двигателем для работы с искусственным интеллектом. Яркие иллюстрации и простые примеры кода избавят вас от необходимости вникать в сложные аспекты конструирования моделей глубокого обучения, делая сложные задачи доступными и увлекательными…...
СПб.: Питер, 2020. — 496 с. Эта книга – подробное руководство по новейшим инструментам глубокого обучения с подкреплением и их ограничениям. Мы реализуем и проверим на практике методы кросс-энтропии и итерации по ценностям (Q-learning), а также градиенты по стратегиям. Для экспериментов используются самые разные среды обучения с подкреплением (RL), начиная с классических...
Пер. с англ. Андрея Логунова. — СПб.: БХВ-Петербург, 2020. — 368 с.: ил. — ISBN: 978-5-9775-4118-3. Затронуты расширенные темы глубокого обучения: оптимизационные алгоритмы, настройка гиперпараметров, отсев и анализ ошибок, стратегии решения типичных задач во время тренировки глубоких нейронных сетей. Описаны простые активационные функции с единственным нейроном (ReLu, сигмоида и...
Пер. с англ. Андрея Логунова. — СПб.: БХВ-Петербург, 2020. — 368 с.: ил. — ISBN: 978-5-9775-4118-3. Затронуты расширенные темы глубокого обучения: оптимизационные алгоритмы, настройка гиперпараметров, отсев и анализ ошибок, стратегии решения типичных задач во время тренировки глубоких нейронных сетей. Описаны простые активационные функции с единственным нейроном (ReLu, сигмоида...
Пер. с англ. Коваленко В.А. — Киев: Диалектика, 2020. — 400 c.: ил. — ISBN: 978-5-907203-59-4. В настоящее время глубокое обучение (Deep Learning) предоставляет средства для распознавания шаблонов в данных, которые являются движущей силой онлайнового бизнеса и общественных медиаплощадок. Книга «Глубокое обучение для чайников» предлагает вам сведения, помогающие снять покров...
Пер. с англ. Коваленко В.А. — Киев: Диалектика, 2020. — 400 c.: ил. — ISBN: 978-5-907203-59-4. В настоящее время глубокое обучение (Deep Learning) предоставляет средства для распознавания шаблонов в данных, которые являются движущей силой онлайнового бизнеса и общественных медиаплощадок. Книга «Глубокое обучение для чайников» предлагает вам сведения, помогающие снять покров...
СПб.: Питер, 2018. — 480 с. Перед вами - первая книга о глубоком обучении, написанная на русском языке. Глубокие модели оказались ключом, который подходит ко всем замкам сразу: новые архитектуры и алгоритмы обучения, а также увеличившиеся вычислительные мощности и появившиеся огромные наборы данных, привели к революционным прорывам в компьютерном зрении, распознавании речи,...
СПб.: Питер, 2018. — 480 с. — ISBN: 978-5-496-02536-2. Перед вами - первая книга о глубоком обучении, написанная на русском языке. Глубокие модели оказались ключом, который подходит ко всем замкам сразу: новые архитектуры и алгоритмы обучения, а также увеличившиеся вычислительные мощности и появившиеся огромные наборы данных, привели к революционным прорывам в компьютерном...
СПб.: Питер, 2018. — 480 с. — ISBN: 978-5-496-02536-2. Первая книга о глубоком обучении, написанная на русском языке. Глубокие модели оказались ключом, который подходит ко всем замкам сразу: новые архитектуры и алгоритмы обучения, а также увеличившиеся вычислительные мощности и появившиеся огромные наборы данных, привели к революционным прорывам в компьютерном зрении,...
М.: ДМК Пресс, 2020. — 372 с.: ил. — ISBN: 978-5-97060-769-5. Древняя стратегическая игра го представляет собой отличный пример для демонстрации возможностей искусственного интеллекта. В 2016 году система, основанная на принципах глубокого обучения, потрясла мир го, победив одного из чемпионов. Вскоре после этого модернизированный алгоритм AlphaGo Zero сокрушил оригинальную...
М.: ДМК Пресс, 2018. — 419 с. Интерес к машинному обучению зашкаливает, но завышенные ожидания нередко губят проекты еще на ранней стадии. Как машинное обучение — и особенно глубокие нейронные сети — может изменить вашу организацию? Эта книга не только содержит практически полезную информацию о предмете, но и поможет приступить к созданию эффективных сетей глубокого обучения....
Пер. с анг. А. А. Слинкина. — М.: ДМК Пресс, 2018. — 420 с.: ил. — ISBN: 978-5-97060-481-6. Все, что должен знать разработчик-практик, чтобы приступить к применению глубокого обучения для решения реальных задач! Интерес к машинному обучению зашкаливает, но завышенные ожидания нередко губят проекты еще на ранней стадии. Как машинное обучение - и особенно глубокие нейронные сети...
Пер. с анг. А. А. Слинкина. — М.: ДМК Пресс, 2018. — 420 с.: ил. — ISBN: 978-5-97060-481-6. Все, что должен знать разработчик-практик, чтобы приступить к применению глубокого обучения для решения реальных задач! Интерес к машинному обучению зашкаливает, но завышенные ожидания нередко губят проекты еще на ранней стадии. Как машинное обучение - и особенно глубокие нейронные сети...
СПб.: Питер, 2019. — 320 с. Глубокое обучение с подкреплением (Reinforcement Learning) - самое популярное и перспективное направление искусственного интеллекта. Практическое изучение RL на Python поможет освоить не только базовые, но и передовые алгоритмы глубокого обучения с подкреплением. Вы начнете с основных принципов обучения с подкреплением, OpenAI Gym и TensorFlow,...
СПб.: Питер, 2019. — 320 с. Глубокое обучение с подкреплением (Reinforcement Learning) - самое популярное и перспективное направление искусственного интеллекта. Практическое изучение RL на Python поможет освоить не только базовые, но и передовые алгоритмы глубокого обучения с подкреплением. Вы начнете с основных принципов обучения с подкреплением, OpenAI Gym и TensorFlow,...
СПб.: Питер, 2019. — 352 с.: ил. — (Библиотека программиста). — ISBN: 978-5-4461-1334-7. Глубокое обучение — это раздел искусственного интеллекта, цель которого научить компьютеры обучаться с помощью нейронных сетей — технологии, созданной по образу и подобию человеческого мозга. Онлайн-переводчики, беспилотные автомобили, рекомендации по выбору товаров именно для вас и...
ДMK, 2022. — 540 c. В книге рассматриваются актуальные примеры создания приложений глубокого обучения с учетом десятилетнего опыта работы автора в этой области. Вы сэкономите часы проб и ошибок, воспользовавшись представленными здесь шаблонами и приемами. Проверенные методики, образцы исходного кода и блестящий стиль повествования позволят с увлечением освоить даже непростые...
2-е изд. — Астана: Спринт Букс, 2024. — 448 с. — ISBN 978-601-08-3729. Генеративный ИИ — одна из самых обсуждаемых тем в сфере технологий. Пора разобраться с возможностями TensorFlow и Keras, чтобы с легкостью создавать впечатляющие генеративные модели глубокого обучения, включая вариационные автокодировщики (VAE), генеративно-состязательные сети (GAN), трансформеры,...
Пер. с англ. А. Киселев. — СПб.: Питер, 2020. — 336 с.: ил. — (Бестселлеры O’Reilly). — ISBN: 978-5-4461-1566-2. Генеративное моделирование — одна из самых обсуждаемых тем в области искусственного интеллекта. Машины можно научить рисовать, писать и сочинять музыку. Вы сами можете посадить искусственный интеллект за парту или мольберт, для этого достаточно познакомиться с самыми...
СПб.: Питер, 2020. — 336 с.: ил. — (Серия «Бестселлеры O’Reilly»). — ISBN: 978-5-4461-1566-2 Генеративное моделирование — одна из самых обсуждаемых тем в области искусственного интеллекта. Машины можно научить рисовать, писать и сочинять музыку. Вы сами можете посадить искусственный интеллект за парту или мольберт, для этого достаточно познакомиться с самыми актуальными...
Пер. с англ. — СПб.: Диалектика, 2020. — 192 с.: ил. — ISBN: 978-5-907203-10-5. Автор этой книги Евгений Черняк — давний исследователь искусственного интеллекта, специализирующийся на обработке естественного языка, революцию в котором сделало глубокое обучение. К сожалению, ему потребовалось много времени, чтобы это понять. Можно сказать в его оправдание, что нейронные сети...
Пер. с англ. и ред. В.А. Коваленка — СПб.: Диалектика, 2020. — 192 с.: ил. — ISBN: 978-5-907203-10-5. Автор этой книги Евгений Черняк — давний исследователь искусственного интеллекта, специализирующийся на обработке естественного языка, революцию в котором сделало глубокое обучение. К сожалению, ему потребовалось много времени, чтобы это понять. Можно сказать в его оправдание,...
СПб.: Питер, 2018. — 400 с.: ил. — (Библиотека программиста). — ISBN: 978-5-4461-0770-4. Глубокое обучение — Deep learning — это набор алгоритмов машинного обучения, которые моделируют высокоуровневые абстракции в данных, используя архитектуры, состоящие из множества нелинейных преобразований. Согласитесь, эта фраза звучит угрожающе. Но всё не так страшно, если о глубоком...
СПб.: Питер, 2018. — 400 с.: ил. — (Библиотека программиста). — ISBN: 978-5-4461-0770-4. Глубокое обучение — Deep learning — это набор алгоритмов машинного обучения, которые моделируют высокоуровневые абстракции в данных, используя архитектуры, состоящие из множества нелинейных преобразований. Согласитесь, эта фраза звучит угрожающе. Но всё не так страшно, если о глубоком...
СПб.: Питер, 2018. — 400 с.: ил. — (Библиотека программиста). — ISBN: 978-5-4461-0770-4. Глубокое обучение — Deep learning — это набор алгоритмов машинного обучения, которые моделируют высокоуровневые абстракции в данных, используя архитектуры, состоящие из множества нелинейных преобразований. Согласитесь, эта фраза звучит угрожающе. Но всё не так страшно, если о глубоком...
2-е изд. — Питер, 2023. — 576 c. Глубокое обучение динамично развивается, открывая все новые и новые возможности создания ПО. Это не только автоматический перевод текстов с одного языка на другой, распознавание изображений, но и многое другое. Глубокое обучение превратилось в важный навык, необходимый каждому разработчику. Keras и TensorFlow облегчают жизнь разработчикам и...
2-е межд. издание. — СПб.: Питер, 2023. — 576 с.: ил. — (Библиотека программиста). — ISBN 978-5-4461-1909-7. Глубокое обучение динамично развивается, открывая все новые и новые возможности создания ПО. Это не только автоматический перевод текстов с одного языка на другой, распознавание изображений, но и многое другое. Глубокое обучение превратилось в важный навык, необходимый...
СПб.: Питер, 2018. — 400 с.: ил. — (Серия «Библиотека программиста»). ISBN: 978-5-4461-0902-9. Глубокое обучение - Deep learning - это набор алгоритмов машинного обучения, которые моделируют высокоуровневые абстракции в данных, используя архитектуры, состоящие из множества нелинейных преобразований. Согласитесь, эта фраза звучит угрожающе. Но всё не так страшно, если о глубоком...
СПб.: Питер, 2018. — 400 с.: ил. — (Библиотека программиста). — ISBN: 978-5-4461-0902-9. Глубокое обучение - Deep learning - это набор алгоритмов машинного обучения, которые моделируют высокоуровневые абстракции в данных, используя архитектуры, состоящие из множества нелинейных преобразований. Согласитесь, эта фраза звучит угрожающе. Но всё не так страшно, если о глубоком...
Москва: ДМК Пресс, 2022. — 648 c. Что такое глубокое обучение? Математические основы нейронных сетей. Введение в Keras и TensorFlow. Примеры работы с нейросетью: классификация и регрессия. Основы машинного обучения. Обобщенный рабочий процесс машинного обучения. Работа с Keras: углубленные навыки. Глубокое обучение в компьютерном зрении. Глубокое обучение для компьютерного...
2-е издание. — Москва: ДМК Пресс, 2022. — 648 с. — ISBN 978-5-93700-189-4. Перед вами второе, расширенное в 1.5 раза издание бестселлера от автора библиотеки Keras. Умение работать с моделями глубокого обучения стало важным навыком современных ученых, исследователей и программистов. API языка R для Keras и TensorFlow делает глубокое обучение доступным для всех пользователей R,...
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