Machine Learning Workbooks

This evening I have started posting on GitHub my series of workbooks that I have been creating as educational material that can be used to teach introductory machine learning independently or in a workshop environment.

Inspired by the pedagogy of Mine Çetinkaya-Rundel (see link), these aim to expose students to the results and findings of analysis and then learn the building blocks of the methods and techniques along the way. They focus on EDA, modeling, inference, and leverage modern computing and assume little background in the topic. They “Start with cake”, by demonstrating where students are aiming to get to by the end of the workbook, so that they have a clear aim and direction for the learning. They leverage visualisation as a key way to engage and educate - and allow for students to leverage their intuition for interpretations.

As these are something I make in my spare time under an open educational licence, they will be added to slowly, but hopefully by making them partly open-source (for now I’m keeping the answers private), people other than my students/apprentices can still benefit from them.