If you are new to scikit-learn, or looking to strengthen your understanding, we highly recommend the scikit-learn MOOC (Massive Open Online Course).
The MOOC, created and maintained by some of the scikit-learn core-contributors, is free of charge and is designed to help learners of all levels master machine learning using scikit-learn. It covers topics from the fundamental machine learning concepts to more advanced areas like predictive modeling pipelines and model evaluation.
The course materials are available on the scikit-learn MOOC website.
This course is also hosted on the FUN platform, which additionally makes the content interactive without the need to install anything, and gives access to a discussion forum.
The videos are available on the Inria Learning Lab channel in a playlist.
14.2. Videos#The scikit-learn YouTube channel features a playlist of videos showcasing talks by maintainers and community members.
For those that are still new to the scientific Python ecosystem, we highly recommend the Python Scientific Lecture Notes. This will help you find your footing a bit and will definitely improve your scikit-learn experience. A basic understanding of NumPy arrays is recommended to make the most of scikit-learn.
14.4. External Tutorials#There are several online tutorials available which are geared toward specific subject areas:
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