Machine learning toolkit for natural language processing. Written for Lisbon Machine Learning Summer School (lxmls.it.pt). This covers

• Scientific Python and Mathematical background
• Linear Classifiers
• Sequence Models
• Structured Prediction
• Syntax and Parsing
• Feed-forward models in deep learning
• Sequence models in deep learning

Machine learning toolkit for natural language processing. Written for LxMLS - Lisbon Machine Learning Summer School

• Use the student branch not this one!

If you are new to Python, the simplest method is to use Anacondato handle your packages, just go to

https://www.anaconda.com/download/

and follow the instructions. If you prefer pip, install the toolkit modules in a virtual environment

virtualenv venv
source venv/bin/activate
pip install pip setuptools --upgrade
pip install -r requirements.txt

In both cases, you will need to get a pip or conda command for your platform for pytorch from http://pytorch.org/ and apply them.

Finally call

python setup.py develop

to install the toolkit in a way that is modifiable.

Bear in mind that the main purpose of the toolkit is educative. You may resort to other toolboxes if you are looking for efficient implementations of the algorithms described.

• Run from the project root directory. If an importing error occurs, try first adding the current path to the PYTHONPATH environment variable, e.g.:
  • export PYTHONPATH=.

To run the all tests install tox and pytest

pip install tox pytest

and run

tox

Note, to combine the coverage data from all the tox environments run:

• Windows

  set PYTEST_ADDOPTS=--cov-append
  tox
  

• Other

  PYTEST_ADDOPTS=--cov-append tox