Mathematical Aspects of Deep Learning

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Mathematical Aspects of Deep Learning is written by Philipp Grohs and published by Cambridge University Press. It's available with International Standard Book Number or ISBN identification 1009035681 (ISBN 10) and 9781009035682 (ISBN 13).

In recent years the development of new classification and regression algorithms based on deep learning has led to a revolution in the fields of artificial intelligence, machine learning, and data analysis. The development of a theoretical foundation to guarantee the success of these algorithms constitutes one of the most active and exciting research topics in applied mathematics. This book presents the current mathematical understanding of deep learning methods from the point of view of the leading experts in the field. It serves both as a starting point for researchers and graduate students in computer science, mathematics, and statistics trying to get into the field and as an invaluable reference for future research.