Tutorial: Natural Language Processing in Python
This repo contains material for a workshop on Natural Language Processing with Python.
Environment Set up
The code has been tested with Python 3.4 and 3.5. This paragraph describes how to set up your environment locally.
Step 1 - clone this repo:
git clone https://github.com/bonzanini/nlp-tutorial cd nlp-tutorial
Step 2 - create and activate a Python virtual environment:
virtualenv nlp-venv source nlp-venv/bin/activate
Step 2 (alternative) - create a Conda environment:
conda create --name nlp-venv python=3.5 source activate nlp-venv
Step 3 - install libraries:
pip install -r requirements.txt
This will download and install NLTK, scikit-learn and jupyter (plus dependencies).
NLTK requires some data to be installed separately (more details on the NLTK website).
From the command line, you can download the required packages:
python -m nltk.downloader punkt stopwords reuters
Alternatively, from a Python interactive shell:
>>> import nltk >>> nltk.download()
Then use the GUI to select the requires packages (punkt, stopwords, reuters).
Tip: even if you can use "all" as package name to install all the NLTK data, it's not a great thing to do over a flakey conference wi-fi. This will download approx. 2Gb and if we all do it at the same time we'll kill the conference wi-fi :)
Finally - run Jupyter:
jupyter notebook
Authors
Main authors:
- Marco Bonzanini (@MarcoBonzanini)
- Miguel Martinez-Alvarez (@MiguelMAlvarez)
Slides
PyCon UK 2016 Tutorial: presentations/pyconuk-slides.pdf
License
Code (mainly in notebooks folder) under MIT license.
Documentation and slides under CC-BY license.
Data
- Documents in data/recipes are public domain from Project Gutenberg
- Documents in data/pyconuk2016 are the abstracts from https://github.com/PyconUK/2016.pyconuk.org