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Deep Learning with PyTorch

You're reading from Deep Learning with PyTorch

Product type Book

Published in Feb 2018

Publisher Packt

ISBN-13 9781788624336

Pages 262 pages

Edition 1st Edition

Languages

Concepts

Author (1):

Vishnu Subramanian

Table of Contents (11) Chapters

Preface

1. Getting Started with Deep Learning Using PyTorch

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

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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

© 2018 Packt Publishing Limited All Rights Reserved

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Authors (1)

Vishnu Subramanian

Vishnu Subramanian has an experience in leading, architecting and implementing several Big Data analytical projects (AI, ML and Deep Learning). Specialized in Machine learning, Deep Learning, Distributed ML, and Visualization. Also, he has experience in domains like Retail, Finance, and Travel and has specialized in understanding and coordinating between Business, AI (Machine Learning, Deep learning) and Engineering teams.

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