The Deep Learning with PyTorch Workshop

封面

版权信息

Experience the Workshop Online

Preface

1. Introduction to Deep Learning and PyTorch

Introduction

Why Deep Learning?

Introduction to PyTorch

Summary

2. Building Blocks of Neural Networks

Introduction

Introduction to Neural Networks

Data Preparation

Building a Deep Neural Network

Summary

3. A Classification Problem Using DNN

Introduction

Problem Definition

Dealing with an Underfitted or Overfitted Model

Deploying Your Model

Summary

4. Convolutional Neural Networks

Introduction

Building a CNN

Data Augmentation

Batch Normalization

Summary

5. Style Transfer

Introduction

Style Transfer

Implementation of Style Transfer Using the VGG-19 Network Architecture

Summary

6. Analyzing the Sequence of Data with RNNs

Introduction

Recurrent Neural Networks

Long Short-Term Memory Networks

LSTM Networks in PyTorch

Natural Language Processing

Sentiment Analysis in PyTorch

Summary

Appendix

1. Introduction to Deep Learning and PyTorch

2. Building Blocks of Neural Networks

3. A Classification Problem Using DNNs

4. Convolutional Neural Networks

5. Style Transfer