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.

• 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