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Python Deep Learning

You're reading from   Python Deep Learning Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow

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Product type Paperback
Published in Jan 2019
Publisher Packt
ISBN-13 9781789348460
Length 386 pages
Edition 2nd Edition
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Authors (5):
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Gianmario Spacagna Gianmario Spacagna
Author Profile Icon Gianmario Spacagna
Gianmario Spacagna
Daniel Slater Daniel Slater
Author Profile Icon Daniel Slater
Daniel Slater
Valentino Zocca Valentino Zocca
Author Profile Icon Valentino Zocca
Valentino Zocca
Peter Roelants Peter Roelants
Author Profile Icon Peter Roelants
Peter Roelants
Ivan Vasilev Ivan Vasilev
Author Profile Icon Ivan Vasilev
Ivan Vasilev
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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. Computer Vision with Convolutional Networks 5. Advanced Computer Vision 6. Generating Images with GANs and VAEs 7. Recurrent Neural Networks and Language Models 8. Reinforcement Learning Theory 9. Deep Reinforcement Learning for Games 10. Deep Learning in Autonomous Vehicles 11. Other Books You May Enjoy

The need for neural networks

Neural networks have been around for many years, and they've gone through several periods during which they've fallen in and out of favor. But recently, they have steadily gained ground over many other competing machine learning algorithms. This resurgence is due to having computers that are fast, the use of graphical processing units (GPUs) versus the most traditional use of computing processing units (CPUs), better algorithms and neural net design, and increasingly larger datasets that we'll see in this book. To get an idea of their success, let's take the ImageNet Large-Scale Visual Recognition Challenge (http://image-net.org/challenges/LSVRC/, or just ImageNet). The participants train their algorithms using the ImageNet database. It contains more than one million high-resolution color images in over a thousand categories (one...

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