Contributing for the first time to a rich package like scikit-learn can seem like an exciting but daunting task. In addition to a large codebase, you must get acquainted with the developer experience and review process to make a contribution.
Finding a good first issue in itself is challenging! With many people all around the world wanting to be a part of it, finding a well defined issue to fix or a feature to develop is often not obvious.
This tutorial is a collection of notes written while contributing to scikit-learn for the first time myself. These notes are a simple revamp of some existing documentation, plus some helpful material.
I hope this minimalistic guide will help you in your journey :)
❶ Start here to get your local environment running
❷ How to contribute
❸ Develop your own estimators