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: J. Guy Davidson and Kate Gregory
Publisher: Addison-Wesley Professional
Date: December 2021
Pages: 352
ISBN: 978-0137647842
Print: 0137647840
Kindle: B09HTH1X38
Audience: C++ developers
Rating: 5
Reviewer: Mike James
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Author: Eric Matthes
Publisher: No Starch Press
Pages: 552
ISBN: 978-1718502703
Print: 1718502702
Kindle: B09WJX22TV
Audience: People wanting to learn Python
Level: Introductory/Intermediate
Audience: Not the complete beginner
Rating: 4
Reviewer: Alex Armstrong
To reach a third edition this [ ... ]


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