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Deep Learning with PyTorch

You're reading from   Deep Learning with PyTorch A practical approach to building neural network models using PyTorch

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Product type Paperback
Published in Feb 2018
Publisher Packt
ISBN-13 9781788624336
Length 262 pages
Edition 1st Edition
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Author (1):
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Vishnu Subramanian Vishnu Subramanian
Author Profile Icon Vishnu Subramanian
Vishnu Subramanian
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Table of Contents (11) Chapters Close

Preface 1. Getting Started with Deep Learning Using PyTorch FREE CHAPTER 2. Building Blocks of Neural Networks 3. Diving Deep into Neural Networks 4. Fundamentals of Machine Learning 5. Deep Learning for Computer Vision 6. Deep Learning with Sequence Data and Text 7. Generative Networks 8. Modern Network Architectures 9. What Next? 10. Other Books You May Enjoy

Generative Networks

All the examples that we have seen in the previous chapters were focused on solving problems such as classification or regression. This chapter is very interesting and important for understanding how deep learning is being evolved to solve problems in unsupervised learning.

In this chapter, we will train networks that learn how to create:

  • Images based on content and a particular artistic style, popularly called style transfer
  • Generating faces of new persons using a particular type of generative adversarial network (GAN)
  • Generating new text using language modeling

These techniques form the basis of most of the advanced research that is happening in the deep learning space. Going into the exact specifics of each of the subfields, such as GANs and language modeling is out of the scope of this book, as they deserve a separate book for themselves. We will learn...

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