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https://github.com/spro/practical-pytorch

Go to https://github.com/pytorch/tutorials - this repo is deprecated and no longer maintained
https://github.com/spro/practical-pytorch

natural-language-generation natural-language-processing nlg nlp seq2seq

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Go to https://github.com/pytorch/tutorials - this repo is deprecated and no longer maintained

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README 

        
**These tutorials have been merged into [the official PyTorch tutorials](https://github.com/pytorch/tutorials). Please go there for better maintained versions of these tutorials compatible with newer versions of PyTorch.**



---



![Practical Pytorch](https://i.imgur.com/eBRPvWB.png)



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](https://github.com/spro/practical-pytorch/blob/master/char-rnn-classification/char-rnn-classification.ipynb)

* [Generating Shakespeare with a Character-Level RNN](https://github.com/spro/practical-pytorch/blob/master/char-rnn-generation/char-rnn-generation.ipynb)

* [Generating Names with a Conditional Character-Level RNN](https://github.com/spro/practical-pytorch/blob/master/conditional-char-rnn/conditional-char-rnn.ipynb)

* [Translation with a Sequence to Sequence Network and Attention](https://github.com/spro/practical-pytorch/blob/master/seq2seq-translation/seq2seq-translation.ipynb)

* [Exploring Word Vectors with GloVe](https://github.com/spro/practical-pytorch/blob/master/glove-word-vectors/glove-word-vectors.ipynb)

* *WIP* Sentiment Analysis with a Word-Level RNN and GloVe Embeddings



#### 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](https://www.continuum.io/anaconda-overview):

```

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

```



## Recommended Reading



### PyTorch basics



* http://pytorch.org/ For installation instructions

* [Offical PyTorch tutorials](http://pytorch.org/tutorials/) for more tutorials (some of these tutorials are included there)

* [Deep Learning with PyTorch: A 60-minute Blitz](http://pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html) to get started with PyTorch in general

* [Introduction to PyTorch for former Torchies](https://github.com/pytorch/tutorials/blob/master/Introduction%20to%20PyTorch%20for%20former%20Torchies.ipynb) if you are a former Lua Torch user

* [jcjohnson's PyTorch examples](https://github.com/jcjohnson/pytorch-examples) for a more in depth overview (including custom modules and autograd functions)



### Recurrent Neural Networks



* [The Unreasonable Effectiveness of Recurrent Neural Networks](http://karpathy.github.io/2015/05/21/rnn-effectiveness/) shows a bunch of real life examples

* [Deep Learning, NLP, and Representations](http://colah.github.io/posts/2014-07-NLP-RNNs-Representations/) for an overview on word embeddings and RNNs for NLP

* [Understanding LSTM Networks](http://colah.github.io/posts/2015-08-Understanding-LSTMs/) is about LSTMs work specifically, but also informative about RNNs in general



### Machine translation



* [Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation](http://arxiv.org/abs/1406.1078)

* [Sequence to Sequence Learning with Neural Networks](http://arxiv.org/abs/1409.3215)



### Attention models



* [Neural Machine Translation by Jointly Learning to Align and Translate](https://arxiv.org/abs/1409.0473)

* [Effective Approaches to Attention-based Neural Machine Translation](https://arxiv.org/abs/1508.04025)



### Other RNN uses



* [A Neural Conversational Model](http://arxiv.org/abs/1506.05869)



### Other PyTorch tutorials



* [Deep Learning For NLP In PyTorch](https://github.com/rguthrie3/DeepLearningForNLPInPytorch)



## Feedback



If you have ideas or find mistakes [please leave a note](https://github.com/spro/practical-pytorch/issues/new).