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Deep Learning: Foundations and Concepts by Christopher M. Bishop Hardcover Book

Description: Deep Learning by Christopher M. Bishop, Hugh Bishop This book offers a comprehensive introduction to the central ideas that underpin deep learning. FORMAT Hardcover CONDITION Brand New Publisher Description 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 specialization. The field of deep learning is undergoing rapid evolution, and therefore this book focusses on ideas that are likely to endure the test of time.The book is organized into numerous bite-sized chapters, each exploring a distinct topic, and the narrative follows a linear progression, with each chapter building upon content from its predecessors. This structure is well-suited to teaching a two-semester undergraduate or postgraduate machine learning course, while remaining equally relevant to those engaged in active research or in self-study.A full understanding of machine learning requires some mathematical background and so the book includes a self-contained introduction to probability theory. However, the focus of the book is on conveying a clear understanding of ideas, with emphasis on the real-world practical value of techniques rather than on abstract theory. Complex concepts are therefore presented from multiple complementary perspectives including textual descriptions, diagrams, mathematical formulae, and pseudo-code.Chris Bishop is a Technical Fellow at Microsoft and is the Director of Microsoft Research AI4Science. He is a Fellow of Darwin College Cambridge, a Fellow of the Royal Academy of Engineering, and a Fellow of the Royal Society. Hugh Bishop is an Applied Scientist at Wayve, a deep learning autonomous driving company in London, where he designs and trains deep neural networks. He completed his MPhil in Machine Learning and Machine Intelligence at Cambridge University."Chris Bishop wrote a terrific textbook on neural networks in 1995 and has a deep knowledge of the field and its core ideas. His many years of experience in explaining neural networks have made him extremely skillful at presenting complicated ideas in the simplest possible way and it is a delight to see these skills applied to the revolutionary new developments in the field." -- Geoffrey Hinton"With the recent explosion of deep learning and AI as a research topic, and the quickly growing importance of AI applications, a modern textbook on the topic was badly needed. The "New Bishop" masterfully fills the gap, covering algorithms for supervised and unsupervised learning, modern deep learning architecture families, as well as how to apply all of this to various application areas." – Yann LeCun"This excellent and very educational book will bring the reader up to date with the main concepts and advances in deep learning with a solid anchoring in probability. Theseconcepts are powering current industrial AI systems and are likely to form the basis of further advances towards artificial general intelligence." -- Yoshua Bengio Author Biography Chris Bishop is a Technical Fellow at Microsoft and is the Director of Microsoft Research AI4Science. He is a Fellow of Darwin College, Cambridge, a Fellow of the Royal Academy of Engineering, a Fellow of the Royal Society of Edinburgh, and a Fellow of the Royal Society of London. He is a keen advocate of public engagement in science, and in 2008 he delivered the prestigious Royal Institution Christmas Lectures, established in 1825 by Michael Faraday, and broadcast on prime-time national television. Chris was a founding member of the UK AI Council and was also appointed to the Prime Ministers Council for Science and Technology.Hugh Bishop is an Applied Scientist at Wayve, an end-to-end deep learning based autonomous driving company in London, where he designs and trains deep neural networks. Before working at Wayve, he completed his MPhil in Machine Learning and Machine Intelligence in the engineering department at Cambridge University. Hugh also holds an MEng in Computer Science from the University of Durham, where he focused his projects on deep learning. During his studies, he also worked as an intern at FiveAI, another autonomous driving company in the UK, and as a Research Assistant, producing educational interactive iPython notebooks for machine learning courses at Cambridge University. Table of Contents Preface.- The Deep Learning Revolution.- Probabilities.- Standard Distributions.- Single-layer Networks: Regression.- Single-layer Networks: Classification.- Deep Neural Networks.- Gradient Descent.- Backpropagation.- Regularization.- Convolutional Networks.- Structured Distributions.- Transformers.- Graph Neural Networks.- Sampling.- Discrete Latent Variables.- Continuous Latent Variables.- Generative Adversarial Networks.- Normalizing Flows.- Autoencoders.- Diffusion Models.- Appendix A Linear Algebra.- Appendix B Calculus of Variations.- Appendix C Lagrange Multipliers.- Biblyography.- Index Details ISBN3031454677 Author Hugh Bishop Publisher Springer International Publishing AG ISBN-13 9783031454677 Format Hardcover Imprint Springer International Publishing AG Subtitle Foundations and Concepts Place of Publication Cham Country of Publication Switzerland Audience Professional & Vocational Year 2023 Pages 649 Publication Date 2023-11-02 Illustrations 400 Illustrations, color; 200 Illustrations, black and white; XX, 649 p. 600 illus., 400 illus. in color. ISBN-10 3031454677 UK Release Date 2023-11-02 DEWEY 006.31 Edition Description 2024 ed. Edition 2024th We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:160480681;

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Deep Learning: Foundations and Concepts by Christopher M. Bishop Hardcover Book

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