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商品詳細

Mathematical Theory of Deep Learning.

Mathematical Theory of Deep Learning.

【Open Accessタイトル】

・ISBN 978-3-032-39921-2 hard EUR 49.99

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お気に入り
著者・編者Petersen, Philipp / Zech, Jakob,
シリーズ (Mathematics and Artificial Intelligence)
出版社 (Springer Nature Switzerland AG, SZ)
出版年月2027
言語ENG
ニュース番号<A05-93057>

解説

This open access book offers a comprehensive introduction to a wide variety of topics in the mathematical theory of deep learning. These include questions pertaining to the prowess of deep neural networks, the surprising effectiveness of current learning algorithms, and the puzzling capability of huge neural networks to make accurate predictions on unseen data. The text focuses on rigorous but accessible results, and provides deep insights into the reasons why this field has been so successful. The book proves useful for mathematicians with a working knowledge of probability theory, linear algebra, and analysis.