Description: Deep Learning Architectures : A Mathematical Approach, Paperback by Calin, Ovidiu, ISBN 3030367231, ISBN-13 9783030367237, Brand New, Free shipping in the US
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. Th 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, th will be of wide interest to machine learning researchers who are interested in a theoretical understanding of the subject.
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Book Title: Deep Learning Architectures : A Mathematical Approach
Number of Pages: Xxx, 760 Pages
Language: English
Publication Name: Deep Learning Architectures : a Mathematical Approach
Publisher: Springer International Publishing A&G
Subject: Intelligence (Ai) & Semantics, Probability & Statistics / General, Applied
Publication Year: 2021
Item Weight: 52.2 Oz
Type: Textbook
Item Length: 10 in
Author: Ovidiu Calin
Subject Area: Mathematics, Computers
Item Width: 7 in
Series: Springer Series in the Data Sciences Ser.
Format: Trade Paperback
