John Wiley & Sons, Inc., 2025. — 256 p. — ISBN: 978-1-394-26927-3. A 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...
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. — 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...
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...
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,...
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 various practical scenarios. The book begins with an introduction to the core concepts of deep learning. It delves into...
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...
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...
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...
Elsevier, 2024. — 334 p. — ISBN: 978-0-443-21432-5. Applications of Deep Machine Learning in Future Energy Systems push 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...
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...
GitforGits, 2024. — 332 p. — ASIN: B0DM3K9NPC. This is the practical, solution-oriented book for every data scientist, machine learning engineer, and AI engineer 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...
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 best-selling 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...
World Scientific Publishing, 2024. — 493 p. — ISBN: 978-981-12-8649-0. 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 applications. It collates the most recent research advances in 3D...
Manning Publications, 2024. — 410 p. — (Final). — ISBN: 9781633438880. Embark on a journey into the world of JAX, a cutting-edge library that’s revolutionizing 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...