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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

Summary

In this introductory chapter, we explored what artificial intelligence, machine learning, and deep learning are and we discussed the differences between all the three. We also looked at applications powered by them in our day-to-day lives. We dig deeper into why DL is only now becoming more popular. Finally, we gave a gentle introduction to PyTorch, which is a deep learning framework.

In the next chapter, we will train our first neural network in 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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