/lxmls-toolkit

Machine Learning applied to Natural Language Processing Toolkit used in the Lisbon Machine Learning Summer School

Primary LanguagePythonMIT LicenseMIT

Summary

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

Instructions for Students

  • Use the student branch not this one!

  • You do not need to run setup.py or pip install, read instructions in the Day 0 chapter of the LxMLS guide.

Install with Anaconda

The simplest method is to use Anacondato handle your packages as described on Day 0 of the lxmls-guide.

Alternative install with pip and virtualenv

If you like pip, install the toolkit modules

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

Then get the right pip install command for your platform for pytorch from http://pytorch.org/ and apply them. Finally call

python setup.py develop

to instal 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.