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Python Deep Learning

You're reading from   Python Deep Learning Next generation techniques to revolutionize computer vision, AI, speech and data analysis

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Product type Paperback
Published in Apr 2017
Publisher Packt
ISBN-13 9781786464453
Length 406 pages
Edition 1st Edition
Languages
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Authors (4):
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Peter Roelants Peter Roelants
Author Profile Icon Peter Roelants
Peter Roelants
Daniel Slater Daniel Slater
Author Profile Icon Daniel Slater
Daniel Slater
Valentino Zocca Valentino Zocca
Author Profile Icon Valentino Zocca
Valentino Zocca
Gianmario Spacagna Gianmario Spacagna
Author Profile Icon Gianmario Spacagna
Gianmario Spacagna
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Toc

Table of Contents (12) Chapters Close

Preface 1. Machine Learning – An Introduction FREE CHAPTER 2. Neural Networks 3. Deep Learning Fundamentals 4. Unsupervised Feature Learning 5. Image Recognition 6. Recurrent Neural Networks and Language Models 7. Deep Learning for Board Games 8. Deep Learning for Computer Games 9. Anomaly Detection 10. Building a Production-Ready Intrusion Detection System Index

Restricted Boltzmann machines

  • In the early 90s, neural networks had largely gone out of fashion. The bulk of machine learning research was around other techniques, such as random forests and support vector machines. Neural networks with only a single hidden layer were less performant than these other techniques, and it was thought that deeper neural networks were too difficult to train.
  • The resurgence of interest in neural networks was spearheaded by Geoffrey Hinton, who, in 2004, led a team of researchers who proceeded to make a series of breakthroughs using restricted Boltzmann machines (RBM) and creating neural networks with many layers; they called this approach deep learning. Within 10 years, deep learning would go from being a niche technique to dominating every single AI competition. RBMs were part of the big breakthrough, allowing Hinton and others to get world record scores on a variety of image and speech recognition problems.
  • In this section, we will look at the theory of how...
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