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
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