This book sets out to provide a mathematical perspective on some key elements of deep neural networks (DNNs). Leonid Berlyand and Pierre-Emmanuel Jabin's compact textbook offers a view that emphasizes the underlying mathematical ideas. It introduces basic concepts from deep learning in a rigorous  fashion with mathematical definitions of deep neural networks (DNNs), loss functions, the backpropagation algorithm, etc. For each concept they identify the simplest setting that minimizes technicalities but still contains the key mathematics.

<ASIN: 3111024318>

Author: Leonid Berlyand and Pierre-Emmanuel Jabin
Publisher: De Gruyter
Date: April 2023
Pages: 126
ISBN: 978-3111024318
Print: 3111024318
Audience: Developers interested in deep learning
Level: Intermediate
Category: Mathematics and Artificial Intelligence

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