更新时间：2021-07-02 15:00:30
coverpage
Title Page
Copyright and Credits
Deep Learning with PyTorch Quick Start Guide
About Packt
Why subscribe?
Packt.com
Contributors
About the author
About the reviewer
Packt is searching for authors like you
Preface
Who this book is for
What this book covers
To get the most out of this book
Download the example code files
Download the color images
Conventions used
Get in touch
Reviews
Introduction to PyTorch
What is PyTorch?
Installing PyTorch
Digital Ocean
Tunneling in to IPython
Amazon Web Services (AWS)
Basic PyTorch operations
Default value initialization
Converting between tensors and NumPy arrays
Slicing and indexing and reshaping
In place operations
Loading data
PyTorch dataset loaders
Displaying an image
DataLoader
Creating a custom dataset
Transforms
ImageFolder
Concatenating datasets
Summary
Deep Learning Fundamentals
Approaches to machine learning
Learning tasks
Unsupervised learning
Clustering
Principle component analysis
Reinforcement learning
Supervised learning
Classification
Evaluating classifiers
Features
Handling text and categories
Models
Linear algebra review
Linear models
Gradient descent
Multiple features
The normal equation
Logistic regression
Nonlinear models
Artificial neural networks
The perceptron
Computational Graphs and Linear Models
autograd
Computational graphs
Linear regression in PyTorch
Saving models
Activation functions in PyTorch
Multi-class classification example
Convolutional Networks
Hyper-parameters and multilayered networks
Benchmarking models
Convolutional networks
A single convolutional layer
Multiple kernels
Multiple convolutional layers
Pooling layers
Building a single-layer CNN
Building a multiple-layer CNN
Batch normalization
Other NN Architectures
Introduction to recurrent networks
Recurrent artificial neurons
Implementing a recurrent network
Long short-term memory networks
Implementing an LSTM
Building a language model with a gated recurrent unit
Getting the Most out of PyTorch
Multiprocessor and distributed environments
Using a GPU
Distributed environments
torch.distributed
torch.multiprocessing
Optimization techniques
