Catalogue of Tools & Metrics for Trustworthy AI

These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.

Machine Learning Glossary



Machine Learning Glossary

How To Contribute

  1. Clone Repo
git clone https://github.com/bfortuner/ml-glossary.git
  1. Install Dependencies
# Assumes you have the usual suspects installed: numpy, scipy, etc..
pip install sphinx sphinx-autobuild
pip install sphinx_rtd_theme
pip install recommonmark

For python-3.x installed, use:

pip3 install sphinx sphinx-autobuild
pip3 install sphinx_rtd_theme
pip3 install recommonmark
  1. Preview Changes

If you are using make build.

cd ml-glossary
cd docs
make html

For Windows.

cd ml-glossary
cd docs
build.bat html
  1. Verify your changes by opening the index.html file in _build/
  2. Submit Pull Request

Short for time?

Feel free to raise an issue to correct errors or contribute content without a pull request.

Style Guide

Each entry in the glossary MUST include the following at a minimum:

  1. Concise explanation – as short as possible, but no shorter
  2. Citations – Papers, Tutorials, etc.

Excellent entries will also include:

  1. Visuals – diagrams, charts, animations, images
  2. Code – python/numpy snippets, classes, or functions
  3. Equations – Formatted with Latex

The goal of the glossary is to present content in the most accessible way possible, with a heavy emphasis on visuals and interactive diagrams. That said, in the spirit of rapid prototyping, it’s okay to to submit a ‘rough draft’ without visuals or code. We expect other readers will enhance your submission over time.

Why RST and not Markdown?

RST has more features. For large and complex documentation projects, it’s the logical choice.

Top Contributors

We’re big fans of Distill and we like their idea of offering prizes for high-quality submissions. We don’t have as much money as they do, but we’d still like to reward contributors in some way for contributing to the glossary. For instance a cheatsheet cryptocurreny where tokens equal commits ;). Let us know if you have better ideas. In the end, this is an open-source project and we hope contributing to a repository of concise, accessible, machine learning knowledge is enough incentive on its own!

Tips and Tricks

Resources

About the tool


Tool type(s):


Country of origin:


Type of approach:





Programming languages:



Github stars:

  • 2462

Github forks:

  • 630

Modify this tool

Use Cases

There is no use cases for this tool yet.

Would you like to submit a use case for this tool?

If you have used this tool, we would love to know more about your experience.

Add use case
catalogue Logos

Disclaimer: The tools and metrics featured herein are solely those of the originating authors and are not vetted or endorsed by the OECD or its member countries. The Organisation cannot be held responsible for possible issues resulting from the posting of links to third parties' tools and metrics on this catalogue. More on the methodology can be found at https://oecd.ai/catalogue/faq.