LxMLS 2023

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
• Reinforcement Learning

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

Instructions for Students

• Use the student branch not this one!

Install with Anaconda or pip

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. We strongly recommend using at least Python 3.

If you prefer pip to Anaconda you can install the toolkit in a way that does not interfere with your existing installation. For this you can use a virtual environment as follows

virtualenv venv
source venv/bin/activate (on Windows: .\venv\Scripts\activate)
pip install pip setuptools --upgrade
pip install --editable . 

This will install the toolkit in a way that is modifiable. If you want to also virtualize you Python version (e.g. you are stuck with Python2 on your system), have a look at pyenv.

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.

Running

• 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=.

Development

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