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Machine Learning
book

Machine Learning

by Sergios Theodoridis
April 2015
Intermediate to advanced content levelIntermediate to advanced
1062 pages
40h 35m
English
Academic Press
Content preview from Machine Learning
Chapter 18

Neural Networks and Deep Learning

Abstract

This chapter deals with neural networks (NN), starting from the early days of the perceptron and perceptron rule, then moves on to review multilayer feed-forward neural networks and the backpropagation algorithm. The drawbacks of training NN with many layers, via the backpropagation algorithm, are discussed together with the advantages that one would expect to obtain if such networks could be trained efficiently. Restricted Boltzmann machines (RBM) are then discussed and the contrastive divergence algorithm is presented as the vehicle to pre-train deep/many layer NN architectures. Deep belief networks, conditional RBMs and autoencoders are also discussed. Finally, two case studies are ...

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Publisher Resources

ISBN: 9780128015223