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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.

Table of Contents

• PyTorch Basics

• Linear Regression

• Logistic Regression

• Feedforward Neural Network

• Convolutional Neural Network

• Deep Residual Network

• Recurrent Neural Network

• Bidirectional Recurrent Neural Network

• Language Model (RNNLM)

• Image Captioning (CNN-RNN)

• Generative Adversarial Network

• Deep Convolutional GAN

• Variational Auto-Encoder (will be updated soon)

• Neural Style Transfer (will be updated soon)

• Deep Q-Network and Q-learning (WIP)

Getting Started

$ git clone https://github.com/yunjey/pytorch-tutorial.git
$ cd pytorch-tutorial/tutorials/project_path
$ python main.py               # cpu version
$ python main-gpu.py           # gpu version

Dependencies

• pytorch
• pytorch-vision