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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 2. Building Blocks of Neural Networks FREE CHAPTER 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

Building Blocks of Neural Networks

Understanding the basic building blocks of a neural network, such as tensors, tensor operations, and gradient descents, is important for building complex neural networks. In this chapter, we will build our first Hello world program in neural networks by covering the following topics:

  • Installing PyTorch
  • Implementing our first neural network
  • Splitting the neural network into functional blocks
  • Walking through each fundamental block covering tensors, variables, autograds, gradients, and optimizers
  • Loading data using PyTorch
You have been reading a chapter from
Deep Learning with PyTorch
Published in: Feb 2018
Publisher: Packt
ISBN-13: 9781788624336
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