| Mathematics of Deep Learning: An Introduction (De Gruyter) |
| Friday, 26 May 2023 | |||
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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.
Author: Leonid Berlyand and Pierre-Emmanuel Jabin
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