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Make Your First GAN With PyTorch

by Make Your First GAN With PyTorch

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Description

A gentle introduction to Generative Adversarial Networks, and a practical step-by-step tutorial on making your own with PyTorch.

This beginner-friendly guide will give you hands-on experience:
  • learning PyTorch basics
  • developing your first PyTorch neural network
  • exploring neural network refinements to improve performance
  • introduce CUDA GPU acceleration
It will introduce GANs, one of the most exciting areas of machine learning:
  • introducing the concept step-by-step, in plain English
  • coding the simplest GAN to develop a good workflow
  • growing our confidence with an MNIST GAN
  • progressing to develop a GAN to generate full-colour human faces
  • experiencing how GANs fail, exploring remedies and improving GAN performance and stability
Beyond the very basics, readers can explore more sophisticated GANs:
  • convolutional GANs for generated higher quality images
  • conditional GANs for generated images of a desired class
The appendices will be useful for students of machine learning as they explain themes often skipped over in many courses:
  • calculating ideal loss values for balanced GANs
  • probability distributions and sampling them to create images
  • carefully chosen examples illustrating how convolutions work
  • a brief explanation of why gradient descent isn't suited to adversarial machine learning
All code is available publicly as open source on github.

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Product Details

  • Mar 14, 2020 Pub Date:
  • 9798624728158 ISBN-13:
  • 9798624728158 ISBN-10:
  • English Language