Apologies for my non-responsiveness. :( I've been heads down at Cruise, buiding ML infra for self-driving cars, and haven't reviewed this repo in forever. Looks like we're getting 54k monthly active users now and I think the repo deserves more attention. Let me know if you would be interested in joining as a maintainer with priviledges to merge PRs.

View The Glossary

1. Clone Repo

git clone https://github.com/bfortuner/ml-glossary.git

2. 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

3. 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

4. Verify your changes by opening the index.html file in _build/

5. Submit Pull Request

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

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.

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

• https://eli.thegreenplace.net/2017/restructuredtext-vs-markdown-for-technical-documentation/

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!

• Adding equations
• Working with Jupyter Notebook
• Quickstart with Jupyter notebook template
• Graphs and charts
• Importing images
• Linking to code

• Desmos Graphing Tool
• 3D Graphing Tool
• How To Submit Pull Requests
• RST Cheatsheet
• Markdown Cheatsheet
• Citation Generator
• MathJax Cheatsheet
• Embedding Math Equations
• Sphinx Tutorial
• Sphinx Docs
• Sphinx Cheatsheet