Mathematical Aspects of Deep Learning (Cambridge University Press)
Friday, 10 February 2023

In recent years the development of new classification and regression algorithms based on deep learning has led to a revolution in the fields of artificial intelligence, machine learning, and data analysis. In this book, Philipp Grohs and Gitta Kutyniok present the current mathematical understanding of deep learning methods from the point of view of the leading experts in the field.

<ASIN:1316516784>

The development of a theoretical foundation to guarantee the success of these algorithms constitutes one of the most active and exciting research topics in applied mathematics.

Author: Philipp Grohs and Gitta Kutyniok
Publisher: Cambridge University Press
Date: February 2023
Pages: 492
ISBN: 978-1316516782
Print:1316516784
Kindle:B0BMW15BV5
Audience: Developers interested in deep learning
Level: Intermediate/Advanced
Category: Mathematics and Artificial Intelligence

 

mathdeep

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Author: Andrew Lock
Publisher: Manning
Date:April 2021
Pages: 832
ISBN: 978-1617298301
Print: 1617298301
Audience: Developers interested in ASP.NET
Rating: 4
Reviewer: Ian Elliot
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Author: Marc Gregoire
Publisher: Wrox
Date: February 2021
Pages: 1312
ISBN: 978-1119695400
Print: 1119695406
Audience: C++ developers
Rating: 4
Reviewer: Mike James


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