Scikit-learn is one of the most popular machine leaning libraries for Python. It provides many unsupervised and supervised learning algorithms that make machine leaning simpler.

We just published a scikit-learn course on the YouTube channel. This course will teach you the basics of scikit-learn so you can start using it in your own machine learning projects.

Vincent D. Warmerdam created this course. Vincent has taught many machine learning concepts on his website and in his job as a research advocate. He has also created some useful open source libraries that work with scikit-learn.

Vincent has a knack for breaking down complex topics in a calm and simple manner.

First, you will get an overview of scikit-learn and learn about some high-level topics.

Next, you will learn about preprocessing tools. Preprocessing has a big impact on the performance of a model.

In the third section you will learn about metrics and how to create custom metrics to judge your machine learning models on.

Then, you will learn about meta estimators. These relate to post-processing your data.

Finally, you will learn about a machine learning library that integrates with scikit-learn and tries to make machine learning more human.

Watch the full course below or on the YouTube channel (2-hour watch).