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Deep Learning with PyTorch Quick Start Guide

You're reading from   Deep Learning with PyTorch Quick Start Guide Learn to train and deploy neural network models in Python

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Product type Paperback
Published in Dec 2018
Publisher Packt
ISBN-13 9781789534092
Length 158 pages
Edition 1st Edition
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David Julian David Julian
Author Profile Icon David Julian
David Julian
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Computational Graphs and Linear Models

By now you should have an understanding of the theory of linear models and neural networks, as well as a knowledge of the fundamentals of PyTorch. In this chapter, we will be putting all this together by implementing some ANNs in PyTorch. We will focus on the implementation of linear models, and show how they can be adapted to perform multi-class classification. We will discuss the following topics in relation to PyTorch:

  • autograd
  • Computational graphs
  • Linear regression
  • Logistic regression
  • Multi-class classification
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