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Mastering PyTorch

You're reading from  Mastering PyTorch

Product type Book
Published in Feb 2021
Publisher Packt
ISBN-13 9781789614381
Pages 450 pages
Edition 1st Edition
Languages
Author (1):
Ashish Ranjan Jha Ashish Ranjan Jha
Profile icon Ashish Ranjan Jha

Table of Contents (20) Chapters

Preface 1. Section 1: PyTorch Overview
2. Chapter 1: Overview of Deep Learning using PyTorch 3. Chapter 2: Combining CNNs and LSTMs 4. Section 2: Working with Advanced Neural Network Architectures
5. Chapter 3: Deep CNN Architectures 6. Chapter 4: Deep Recurrent Model Architectures 7. Chapter 5: Hybrid Advanced Models 8. Section 3: Generative Models and Deep Reinforcement Learning
9. Chapter 6: Music and Text Generation with PyTorch 10. Chapter 7: Neural Style Transfer 11. Chapter 8: Deep Convolutional GANs 12. Chapter 9: Deep Reinforcement Learning 13. Section 4: PyTorch in Production Systems
14. Chapter 10: Operationalizing PyTorch Models into Production 15. Chapter 11: Distributed Training 16. Chapter 12: PyTorch and AutoML 17. Chapter 13: PyTorch and Explainable AI 18. Chapter 14: Rapid Prototyping with PyTorch 19. Other Books You May Enjoy

Technical requirements

We will be using Jupyter notebooks for all of our exercises. And the following is the list of Python libraries that shall be installed for this chapter using pip. For example, run pip install torch==1.4.0 on the command line:

jupyter==1.0.0
torch==1.4.0
torchvision==0.5.0
matplotlib==3.1.2

All code files relevant to this chapter are available at https://github.com/PacktPublishing/Mastering-PyTorch/tree/master/Chapter01.

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Mastering PyTorch
Published in: Feb 2021 Publisher: Packt ISBN-13: 9781789614381
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