PyTorch Tutorial for Deep Learning Researchers

This repository provides tutorial code for deep learning researchers to learn PyTorch. In the tutorial, most of the models were implemented with less than 30 lines of code. Before starting this tutorial, it is recommended to finish Official Pytorch Tutorial.

1. Basics

• PyTorch Basics
• Linear Regression
• Logistic Regression
• Feedforward Neural Network

2. Intermediate

• Convolutional Neural Network
• Deep Residual Network
• Recurrent Neural Network
• Bidirectional Recurrent Neural Network
• Language Model (RNN-LM)

3. Advanced

• Generative Adversarial Networks
• Variational Auto-Encoder
• Neural Style Transfer
• Image Captioning (CNN-RNN)

4. Utilities

• TensorBoard in PyTorch

Getting Started

$ git clone https://github.com/yunjey/pytorch-tutorial.git
$ cd pytorch-tutorial/tutorials/PATH_TO_PROJECT
$ python main.py

Dependencies

• Python 2.7 or 3.5+
• PyTorch 0.4.0+

GitHub - yunjey/pytorch-tutorial: PyTorch Tutorial for Deep Learning Researchers

PyTorch Tutorial for Deep Learning Researchers. Contribute to yunjey/pytorch-tutorial development by creating an account on GitHub.

GitHubyunjey