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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

Installing PyTorch

PyTorch is available as a Python package and you can either use pip, or conda, to build it or you can build it from source. The recommended approach for this book is to use the Anaconda Python 3 distribution. To install Anaconda, please refer to the Anaconda official documentation at https://conda.io/docs/user-guide/install/index.html. All the examples will be available as Jupyter Notebooks in the book's GitHub repository. I would strongly recommend you use Jupyter Notebook, since it allows you to experiment interactively. If you already have Anaconda Python installed, then you can proceed with the following steps for PyTorch installation.

For GPU-based installation with Cuda 8:

conda install pytorch torchvision cuda80 -c soumith

For GPU-based installation with Cuda 7.5:

conda install pytorch torchvision -c soumith

For non-GPU-based installation:

conda...
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