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Python Deep Learning - Second Edition
book

Python Deep Learning - Second Edition

by Ivan Vasilev, Daniel Slater, Gianmario Spacagna, Peter Roelants, Valentino Zocca
January 2019
Intermediate to advanced
386 pages
11h 13m
English
Packt Publishing
Content preview from Python Deep Learning - Second Edition

Deep Learning Fundamentals

In this chapter, we will introduce deep learning(DL) and deep neural networks (DNNs), that is, neural networks with multiple hidden layers. You may wonder what the point of using more than one hidden layer is, given the universal approximation theorem. This is in no way a naive question, and for a long time neural networks were used in that way. Without going into too much detail, one reason is that approximating a complex function might require a huge number of neurons in the hidden layer, making it impractical to use. There is also another, more important, reason for using deep networks, which is not directly related to the number of hidden layers, but to the level of learning. A deep network does not simply learn ...

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Publisher Resources

ISBN: 9781789348460Supplemental Content