scikit-learn is a popular open source machine learning library for Python. I have been using the library for about two years now and finally had the chance to make a minor contribution to its development.
For those that are new to machine learning and/or Python: scikit-learn provides outstanding documentation and a great set of examples demonstrating the development of powerful machine learning pipelines in Python.
Refactoring a couple of unit tests
The scikit-learn development team makes it easy for newcomers to contribute to the project by labelling specific issues listed on GitHub as ‘Easy’. These problems are especially beginner-friendly and a good place to start when first contributing to the library.
About two weeks ago, I decided that I wanted to give back to the community and contribute to the project source code. My first pull request refactored a couple of unit tests (corresponding issue). After a couple of iterations on my changes and very nice feedback from the core developers, my contribution has now been merged with the main code base.
Open source projects can only survive by ongoing support from the community. I will thus try my best to make regular further contibutions to scikit-learn (or other projects) in the future and encourage every reader to do so, too.