NLP-tutorials

Slides and code for the intro to NLP class at the Data Science Retreat @ Berlin, 28 Oct 2019

Installation

Clone this repo with

git clone --recursive https://github.com/davidalbertonogueira/NLP-tutorials
git submodule update --depth 10 --recursive --init

Requirements

Besides python >= 3.7 and pip, the required libraries are listed in requirements.txt.

Code is cross-platform. Tested in Windows and Ubuntu 18.04.

Setting up a virtual environment

Linux	Windows
sudo apt-get install virtualenv / pip install virtualenv	pip install virtualenv
virtualenv --python /usr/bin/python3.7 venv	virtualenv venv
source venv/bin/activate	venv\Scripts\activate.bat
pip install -r requirements.txt	pip install -r requirements.txt
pip install http://download.pytorch.org/whl/cpu/torch-0.4.1-cp37-cp37m-linux_x86_64.whl (1)*	pip install http://download.pytorch.org/whl/cpu/torch-0.4.1-cp37-cp37m-win_amd64.whl (1)*
pip install torchvision	pip install torchvision
pip install torchtext==0.2.3	pip install torchtext==0.2.3
python -m spacy download en_core_web_sm	python -m spacy download en_core_web_sm

(1)* replace "cpu" in link if you plan to use GPU: "cu80" for CUDA 8, "cu90" for CUDA 9.0, "cu92" for CUDA 9.2, ...

If you require a newer version, please visit http://pytorch.org/ and follow their instructions to install the relevant pytorch binary.

Text Classification

Text Classification with BoW + TF-IDF + Naive bayes and SVM based on http://github.com/Gunjitbedi/Text-Classification

Text Classification with word embeddings + neural network

Sentiment Analysis

Sentiment Analysis with task-specific word embeddings + Pytorch neural network

The implemented model is a Deep Bidirectional LSTM model with Attention, based on the work of Baziotis et al., 2017: DataStories at SemEval-2017 Task 4: Deep LSTM with Attention for Message-level and Topic-based Sentiment Analysis.

Recomendation

Recomendation using Colaborative filtering

Named Entity Recognition

Transition-based NER system (in C++ Dynet) (Pytorch version)

Paper: https://arxiv.org/pdf/1603.01360.pdf

Bonus material

Transformers: Attention is all you need copied from http://nlp.seas.harvard.edu/2018/04/03/attention.html

Paper: https://arxiv.org/abs/1706.03762