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.

Classifying Names with a Character-Level RNN Generating Names with a Character-Level RNN :fire: Translation with a Sequence to Sequence Network and Attention WIP Sentiment Analysis with a Word-Level RNN and GloVe Embeddings WIP Sentence Similarity with a Word-Level Autoencoder WIP Intent Parsing with Recursive Application of Recurrent Neural Networks Recommended Reading

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

http://pytorch.org/ For installation instructions Deep Learning with PyTorch: A 60-minute Blitz to get started with PyTorch in general jcjohnson's PyTorch examples for a wide and deep overview Introduction to PyTorch for former Torchies if you are a former Lua Torch user

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

The Unreasonable Effectiveness of Recurrent Neural Networks shows a bunch of real life examples Deep Learning, NLP, and Representations for an overview on word embeddings and RNNs for NLP Understanding LSTM Networks is about LSTMs specifically but also informative about RNNs in general

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

Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation Sequence to Sequence Learning with Neural Networks Neural Machine Translation by Jointly Learning to Align and Translate A Neural Conversational Model 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 .