DeepNLP-models-Pytorch

Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ: NLP with Deep Learning)

This is not for Pytorch beginners. If it is your first time to use Pytorch, I recommend these awesome tutorials.
If you're interested in DeepNLP, I strongly recommend you to work with this awesome lecture.

This material is not perfect but will help your study and research:) Please feel free to pull requests!!

Model	Links
01. Skip-gram-Naive-Softmax	[notebook / data / paper]
02. Skip-gram-Negative-Sampling	[notebook / data / paper]
03. GloVe	[notebook / data / paper]
04. Window-Classifier-for-NER	[notebook / data / paper]
05. Neural-Dependancy-Parser	[notebook / data / paper]
06. RNN-Language-Model	[notebook / data / paper]
07. Neural-Machine-Translation-with-Attention	[notebook / data / paper]
08. CNN-for-Text-Classification	[notebook / data / paper]
09. Recursive-NN-for-Sentiment-Classification	[notebook / data / paper]
10. Dynamic-Memory-Network-for-Question-Answering	[notebook / data / paper]

Requirements

git clone https://github.com/DSKSD/cs-224n-Pytorch.git

cd script
chmod u+x prepare_dataset.sh
./prepare_dataset.sh

ubuntu 16.04 python 3.5.2 with various of ML/DL packages including tensorflow, sklearn, pytorch

docker pull dsksd/deepstudy:0.2

pip3 install docker-compose
cd script
docker-compose up -d

not yet

Sungdong Kim / @DSKSD