• Title: Mathematical Theory of Deep Learning
• Author(s) Philipp Petersen, Jakob Zech
• Publisher: arXiv (October 14, 2024); eBook (Creative Commons Licensed)
• License(s): Creative Commons License (CC)
• Paperback: N/A
• eBook: PDF (275 pages) and PostScript
• Language: English
• ISBN-10/ASIN: N/A
• ISBN-13: N/A
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Book Description

This book provides an introduction to the mathematical analysis of deep learning. It covers fundamental results in approximation theory, optimization theory, and statistical learning theory, which are the three main pillars of deep neural network theory.

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• Deep Learning
• Neural Networks
• Linear and Matrix Algebra
• Calculus and Mathematical Analysis
• Statistics
• Probability and Stochastic Processes

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