Neural Networks and Numerical Analysis

· De Gruyter Series in Applied and Numerical Mathematics Book 6 · Walter de Gruyter GmbH & Co KG
Ebook
174
Pages
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About this ebook

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.

About the author

Bruno Després, Sorbonne University, France.

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