封面
版权页
Why subscribe?
Packt.com
Contributors
About the authors
About the reviewers
Preface
Who this book is for
What this book covers
To get the most out of this book
Get in touch
Chapter 1. Deep Learning Walkthrough and PyTorch Introduction
Understanding PyTorch's history
What is PyTorch?
Using computational graphs
Exploring deep learning
Getting started with the code
Chapter 2. A Simple Neural Network
Introduction to the neural network
The problem
Dataset
Novice model
The PyTorch way
Summary
References
Chapter 3. Deep Learning Workflow
Ideation and planning
Design and experimentation
Model implementation
Training and validation
Summary
References
Chapter 4. Computer Vision
Introduction to CNNs
Computer vision with PyTorch
Chapter 5. Sequential Data Processing
Introduction to recurrent neural networks
The problem
Approaches
Summary
References
Chapter 6. Generative Networks
Defining the approaches
Autoregressive models
GANs
Summary
References
Chapter 7. Reinforcement Learning
The problem
Episodic versus continuous tasks
Cumulative discounted rewards
Markov decision processes
The solution
Summary
References
Chapter 8. PyTorch to Production
Serving with Flask
ONNX
Efficiency with TorchScript
Exploring RedisAI
Summary
References
Index
更新时间：2021-06-11 13:28:31
完结共64章
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