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The Principles Of Deep Learning Theory Daniel A Roberts Sho Yaida

Name: The Principles Of Deep Learning Theory Daniel A Roberts Sho Yaida
SKU: BELL-43230632
Price: 31.00 USD
Availability: InStock
Rating: 4.8 (24 reviews)

SKU: BELL-43230632

$ 31.00 ~~$ 45.00~~ (-31%)

4.8

24 reviews

The Principles Of Deep Learning Theory Daniel A Roberts Sho Yaida instant download after payment.

Publisher: Cambridge University Press

File Extension: PDF

File size: 5.71 MB

Pages: 472

Author: Daniel A. Roberts, Sho Yaida, Boris Hanin

ISBN: 9781316519332, 9781009023405, 1316519333, 1009023403, 2021060635

Language: English

Year: 2022

Product desciption

The Principles Of Deep Learning Theory Daniel A Roberts Sho Yaida by Daniel A. Roberts, Sho Yaida, Boris Hanin 9781316519332, 9781009023405, 1316519333, 1009023403, 2021060635 instant download after payment.

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.