Machine learning toolkit for natural language processing. Written for LxMLS - Lisbon Machine Learning Summer School
- Scientific Python and Mathematical background
- Linear Classifiers (Gradient Descent)
- Feed-forward models in deep learning (Backpropagation)
- Sequence models in deep learning
- Attention Models (Transformers)
Bear in mind that the main purpose of the toolkit is educational. You may resort to other toolboxes if you are looking for efficient implementations of the algorithms described.
- Use the student branch not this one 🚨!
Download the code. If you are used to git just clone the student branch. For example from the command line in do
git clone git@github.com:LxMLS/lxmls-toolkit.git lxmls-toolkit-student
If you do not have a pyhon installation, install miniconda. Go to
https://docs.conda.io/en/latest/miniconda.html
and follow the instructions for installation using Python 3.
After setting up the anaconda:
use your favorite git tool to create a clone of this repository
navigate to the folder where the repository resides
install anaconda (see instruction)
conda create --name lxmls_new
conda activate lxmls_new
conda install pip
pip install --editable .
and follow the instructions for your platform (Windows, Linux, OSX). We reccomend that you create your virtual environment with a recent python version i.e.
cd lxmls-toolkit-student
conda create -y -p ./lxmls2023 python=3.9 -y
conda activate ./lxmls2023
Note the ./
in ./lxmls2023
-- this will install the virtual environment
locally, so if you delete lxmls-toolkit-student
you will also remove the
environment.
Then install the toolkit, just to be sure upgrade your pip (always good)
pip install pip setuptools --upgrade
pip install -r requirements.txt
This will install the toolkit in a way that is modifiable. Remember to run scripts from the root directory lxmls-toolkit-student
- 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
* Other
PYTEST_ADDOPTS=--cov-append tox