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The Principles of Deep Learning Theory: An Effective Theory Approach to Understanding Neural Networks - Hardcover
- PublisherCambridge University Press
- Publication date2022
- ISBN 10 1316519333
- ISBN 13 9781316519332
- BindingHardcover
- LanguageEnglish
- Number of pages472
- Rating
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The Principles of Deep Learning Theory : An Effective Theory Approach to Understanding Neural Networks
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Cambridge University Press, 2022
ISBN 10: 1316519333
ISBN 13: 9781316519332
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Principles of Deep Learning Theory : An Effective Theory Approach to Understanding Neural Networks
Published by
Cambridge University Press, 2022
ISBN 10: 1316519333
ISBN 13: 9781316519332
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The Principles of Deep Learning Theory: An Effective Theory Approach to Understanding Neural Networks
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Cambridge University Press, 2022
ISBN 10: 1316519333
ISBN 13: 9781316519332
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The Principles of Deep Learning Theory
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ISBN 10: 1316519333
ISBN 13: 9781316519332
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The Principles of Deep Learning Theory: An Effective Theory Approach to Understanding Neural Networks
Published by
Cambridge University Press, 2022
ISBN 10: 1316519333
ISBN 13: 9781316519332
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The Principles of Deep Learning Theory
Published by
Cambridge University Press, 2022
ISBN 10: 1316519333
ISBN 13: 9781316519332
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Hardcover
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Principles of Deep Learning Theory : An Effective Theory Approach to Understanding Neural Networks
Published by
Cambridge University Press, 2022
ISBN 10: 1316519333
ISBN 13: 9781316519332
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Hardcover
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The Principles of Deep Learning Theory (Hardcover)
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Cambridge University Press, Cambridge, 2022
ISBN 10: 1316519333
ISBN 13: 9781316519332
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Hardcover. Condition: new. Hardcover. 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 the theoretical forefront accessible, the authors eschew the subject's traditional emphasis on intimidating formality without sacrificing accuracy. Straightforward and approachable, this volume balances detailed first-principle derivations of novel results with insight and intuition for theorists and practitioners alike. This self-contained textbook is ideal for students and researchers interested in artificial intelligence with minimal prerequisites of linear algebra, calculus, and informal probability theory, and it can easily fill a semester-long course on deep learning theory. For the first time, the exciting practical advances in modern artificial intelligence capabilities can be matched with a set of effective principles, providing a timeless blueprint for theoretical research in deep learning. This is the first book focused entirely on deep learning theory. Tools from theoretical physics are borrowed and adapted to explain, from first principles, how realistic deep neural networks work, benefiting practitioners looking to build better AI models and theorists looking for a unifying framework for understanding intelligence. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781316519332
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Principles of Deep Learning Theory : An Effective Theory Approach to Understanding Neural Networks
Published by
Cambridge University Press, 2022
ISBN 10: 1316519333
ISBN 13: 9781316519332
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The Principles of Deep Learning Theory: An Effective Theory Approach to Understanding Neural Networks
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Cambridge University Press, 2022
ISBN 10: 1316519333
ISBN 13: 9781316519332
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