This book describes how neural networks operate from the mathematical point of view. As a result, neural networks can be interpreted both as function universal approximators and information processors. The book bridges the gap between ideas and concepts of neural networks, which are used nowadays at an intuitive level, and the precise modern mathematical language, presenting the best practices of the former and enjoying the robustness and elegance of the latter. This book can be used in a graduate course in deep learning, ...
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This book describes how neural networks operate from the mathematical point of view. As a result, neural networks can be interpreted both as function universal approximators and information processors. The book bridges the gap between ideas and concepts of neural networks, which are used nowadays at an intuitive level, and the precise modern mathematical language, presenting the best practices of the former and enjoying the robustness and elegance of the latter. This book can be used in a graduate course in deep learning, with the first few parts being accessible to senior undergraduates. In addition, the book will be of wide interest to machine learning researchers who are interested in a theoretical understanding of the subject.
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Add this copy of Deep Learning Architectures: a Mathematical Approach to cart. $38.08, good condition, Sold by HPB-Red rated 5.0 out of 5 stars, ships from Dallas, TX, UNITED STATES, published 2021 by Springer.
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Add this copy of Deep Learning Architectures: a Mathematical Approach to cart. $39.35, good condition, Sold by Vive Liber Books rated 5.0 out of 5 stars, ships from Somers, CT, UNITED STATES, published 2021 by Springer.
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Good. Pages are clean with normal wear. May have limited markings & or highlighting within pages & or cover. May have some wear & creases on the cover. The spine may also have minor wear. May not include CD DVD access code or any other supplemental materials.
Add this copy of Deep Learning Architectures: A Mathematical Approach to cart. $42.39, like new condition, Sold by GreatBookPrices rated 4.0 out of 5 stars, ships from Columbia, MD, UNITED STATES, published 2021 by Springer.
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Fine. Trade paperback (US). Glued binding. 760 p. Contains: Unspecified, Illustrations, black & white, Illustrations, color. Springer the Data Sciences. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers.
Add this copy of Deep Learning Architectures: a Mathematical Approach to cart. $43.62, good condition, Sold by BooksRun rated 4.0 out of 5 stars, ships from Philadelphia, PA, UNITED STATES, published 2021 by Springer.
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Good. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
