This book offers a thorough exploration of deep learning, providing both foundational knowledge and practical insights that are essential for anyone interested in this rapidly evolving field. It begins with a comprehensive introduction to deep learning, emphasizing its significance and the transformative impact it has had across various industries. Designed to be accessible to both beginners and experienced practitioners, the book systematically guides readers through the essential concepts and mathematical foundations that underpin deep learning, such as linear algebra, calculus, probability, and information theory. This book then delves into the fundamentals of deep learning, offering a detailed look at supervised, unsupervised, and reinforcement learning. It also covers key evaluation metrics, providing readers with the tools needed to assess the performance of different models effectively. The book explains complex concepts like activation functions, feedforward and backpropagation algorithms, and loss functions in a clear and accessible manner.Overall, this book serves as a comprehensive guide to understanding and applying deep learning.
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Taschenbuch. Condition: Neu. DEEP LEARNING | A Comprehensive Guide | Sharon Susan Jacob | Taschenbuch | Englisch | 2024 | LAP LAMBERT Academic Publishing | EAN 9786208011291 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 130391475
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book offers a thorough exploration of deep learning, providing both foundational knowledge and practical insights that are essential for anyone interested in this rapidly evolving field. It begins with a comprehensive introduction to deep learning, emphasizing its significance and the transformative impact it has had across various industries. Designed to be accessible to both beginners and experienced practitioners, the book systematically guides readers through the essential concepts and mathematical foundations that underpin deep learning, such as linear algebra, calculus, probability, and information theory. This book then delves into the fundamentals of deep learning, offering a detailed look at supervised, unsupervised, and reinforcement learning. It also covers key evaluation metrics, providing readers with the tools needed to assess the performance of different models effectively. The book explains complex concepts like activation functions, feedforward and backpropagation algorithms, and loss functions in a clear and accessible manner.Overall, this book serves as a comprehensive guide to understanding and applying deep learning.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 268 pp. Englisch. Seller Inventory # 9786208011291
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