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Contents

1. PyTorch Basic

  1. basic
  2. variable autograd
  3. Linear Regression Models
  4. NonLinear Models
  5. Classification Models
  6. Batch Tranining

2. Neural Network Basic

  1. Optimizers
  2. NN MNIST
  3. Deep NN MNIST
  4. CNN MNIST
  5. Dropout
  6. RNN

3. Vison

  1. CNN CIFAR-10
  2. Transfer Learning
  3. CNN High resolution images
  4. DCGAN
  5. VAE

4. NLP

  1. Word Embedding
  2. Text classificationw
  3. NNLMW
  4. Seq2Seq
  5. RNN text generation
  6. Reinforcement learning text generation
  7. ELMO
  8. Transformer
  9. BERT
  10. GPT-2
  11. Transformer-XL
  12. XLNet
  13. T5

System requirements

conda install pytorch torchvision cudatoolkit=10.1 -c pytorch
pip install -r requirements.txt

Getting Started

$ git clone https://github.com/gyunggyung/PyTorch.git
$ cd PyTorch
$ jupyter notebook

Other Github

tutorial

book

Vison

NLP

Speech

recommender models

Recommended Reading

PyTorch basics

Recurrent Neural Networks

Machine translation

Attention models

Other RNN uses

Other PyTorch tutorials

Author

gyung/ @gyunggyung