Mathematical Aspects of Deep Learning

Mathematical Aspects of Deep Learning
Author :
Publisher : Cambridge University Press
Total Pages : 494
Release :
ISBN-10 : 9781009035682
ISBN-13 : 1009035681
Rating : 4/5 (82 Downloads)

Book Synopsis Mathematical Aspects of Deep Learning by : Philipp Grohs

Download or read book Mathematical Aspects of Deep Learning written by Philipp Grohs and published by Cambridge University Press. This book was released on 2022-12-22 with total page 494 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.


Mathematical Aspects of Deep Learning Related Books

Mathematical Aspects of Deep Learning
Language: en
Pages: 494
Authors: Philipp Grohs
Categories: Computers
Type: BOOK - Published: 2022-12-22 - Publisher: Cambridge University Press

DOWNLOAD EBOOK

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 intel
Mathematics for Machine Learning
Language: en
Pages: 392
Authors: Marc Peter Deisenroth
Categories: Computers
Type: BOOK - Published: 2020-04-23 - Publisher: Cambridge University Press

DOWNLOAD EBOOK

The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, opti
Math for Deep Learning
Language: en
Pages: 346
Authors: Ronald T. Kneusel
Categories: Computers
Type: BOOK - Published: 2021-12-07 - Publisher: No Starch Press

DOWNLOAD EBOOK

Math for Deep Learning provides the essential math you need to understand deep learning discussions, explore more complex implementations, and better use the de
Math and Architectures of Deep Learning
Language: en
Pages: 550
Authors: Krishnendu Chaudhury
Categories: Computers
Type: BOOK - Published: 2024-05-21 - Publisher: Simon and Schuster

DOWNLOAD EBOOK

Shine a spotlight into the deep learning “black box”. This comprehensive and detailed guide reveals the mathematical and architectural concepts behind deep
Mathematical Aspects of Deep Learning
Language: en
Pages: 493
Authors: Philipp Grohs
Categories: Computers
Type: BOOK - Published: 2022-12-31 - Publisher: Cambridge University Press

DOWNLOAD EBOOK

A mathematical introduction to deep learning, written by a group of leading experts in the field.