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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

How to keep yourself updated

Social media platforms, particularly Twitter, help you to stay updated in the field. There are many people you can follow. If you are unsure of where to start, I would recommend following Jeremy Howard (https://twitter.com/jeremyphoward), and any interesting people he may follow. By doing this, you would be forcing the Twitter recommendation system to work for you.

Another important Twitter account you need to follow is PyTorch's (https://twitter.com/PyTorch). The amazing people behind PyTorch have some great content being shared.

If you are looking for research papers, then look at arxiv-sanity (http://www.arxiv-sanity.com/), where many smart researchers publish their papers.

More great resources for learning about PyTorch are its tutorials (http://pytorch.org/tutorials/), its source code (https://github.com/pytorch/pytorch), and its documentation...

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