9783030367206-3030367207-Deep Learning Architectures: A Mathematical Approach (Springer Series in the Data Sciences)

Deep Learning Architectures: A Mathematical Approach (Springer Series in the Data Sciences)

ISBN-13: 9783030367206
ISBN-10: 3030367207
Edition: 1st ed. 2020
Author: Ovidiu Calin
Publication date: 2020
Publisher: Springer
Format: Hardcover 790 pages
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Book details

ISBN-13: 9783030367206
ISBN-10: 3030367207
Edition: 1st ed. 2020
Author: Ovidiu Calin
Publication date: 2020
Publisher: Springer
Format: Hardcover 790 pages

Summary

Deep Learning Architectures: A Mathematical Approach (Springer Series in the Data Sciences) (ISBN-13: 9783030367206 and ISBN-10: 3030367207), written by authors Ovidiu Calin, was published by Springer in 2020. With an overall rating of 3.9 stars, it's a notable title among other AI & Machine Learning (Computer Science) books. You can easily purchase or rent Deep Learning Architectures: A Mathematical Approach (Springer Series in the Data Sciences) (Hardcover) from BooksRun, along with many other new and used AI & Machine Learning books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $2.53.

Description

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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