June 18, 2019

374 words 2 mins read



PyTorch tutorials demonstrating modern techniques with readable code

repo name spro/practical-pytorch
repo link https://github.com/spro/practical-pytorch
language Jupyter Notebook
size (curr.) 1713 kB
stars (curr.) 3874
created 2017-01-22
license MIT License

These tutorials have been merged into the official PyTorch tutorials. Please go there for better maintained versions of these tutorials compatible with newer versions of PyTorch.

Practical Pytorch

Learn PyTorch with project-based tutorials. These tutorials demonstrate modern techniques with readable code and use regular data from the internet.


Series 1: RNNs for NLP

Applying recurrent neural networks to natural language tasks, from classification to generation.

Series 2: RNNs for timeseries data

  • WIP Predicting discrete events with an RNN

Get Started

The quickest way to run these on a fresh Linux or Mac machine is to install Anaconda:

curl -LO https://repo.continuum.io/archive/Anaconda3-4.3.0-Linux-x86_64.sh
bash Anaconda3-4.3.0-Linux-x86_64.sh

Then install PyTorch:

conda install pytorch -c soumith

Then clone this repo and start Jupyter Notebook:

git clone http://github.com/spro/practical-pytorch
cd practical-pytorch
jupyter notebook

PyTorch basics

Recurrent Neural Networks

Machine translation

Attention models

Other RNN uses

Other PyTorch tutorials


If you have ideas or find mistakes please leave a note.

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