Neural Networks and Numerical Analysis (Hardcover)

This book uses numerical analysis as the main tool to investigate methods in machine learning and neural networks. The efficiency of neural network representations for general functions and for polynomial functions is studied in detail, together with an original description of the Latin hypercube method and of the ADAM algorithm for training. Furthermore, unique features include the use of Tensorflow for implementation session, and the description of on going research about the construction of new optimized numerical schemes.

General

Imprint:	De Gruyter
Country of origin:	Germany
Series:	De Gruyter Series in Applied and Numerical Mathematics
Release date:	September 2022
First published:	2022
Authors:	Bruno Despres
Dimensions:	240 x 170mm (L x W)
Format:	Hardcover
Pages:	174
ISBN-13:	978-3-11-078312-4
Categories:	Books > Science & Mathematics > Mathematics > Numerical analysis Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematical modelling Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning Books > Computing & IT > Applications of computing > Artificial intelligence > Neural networks
LSN:	3-11-078312-6
Barcode:	9783110783124

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