cliffzhao / practical-pytorch

Project based PyTorch tutorials, focused on using neural networks (especially RNNs) for natural language tasks

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Practical Pytorch

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

Tutorials

Series 1: RNNs for NLP

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

Series 2: RNNs for timeseries

  • WIP Predicting future events with an RNN

Recommended Reading

I assume you have at least installed PyTorch, know Python, and understand Tensors:

You should know about Recurrent Neural Networks and how they work:

And for more, read the papers that introduced these topics:

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

Feedback

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

About

Project based PyTorch tutorials, focused on using neural networks (especially RNNs) for natural language tasks

License:MIT License


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Language:Jupyter Notebook 95.1%Language:Python 4.9%