Welcome to the SOWISO class connected with the Math4AI site that is associated with the MSc in Artificial Intelligence from the University of Amsterdam. Math4AI is provided to help you familiarize yourself with the mathematics needed to become proficient in machine learning.

The essential mathematics any student of machine learning should know are linear algebra, multivariate calculus, and statistics. These three areas of mathematics truly form the foundation of all topics in machine learning. That is why our chapters are dedicated to covering the most important topics within these areas for our purposes:

• Linear Algebra, studying how to represent, transform, and analyze high dimensional data as vectors.
• Multivariate Calculus, studying how to do differential calculus in high dimensional spaces.
• Statistics, studying how to analyze data, quantify uncertainty, and describe random events.

Each theory page contains a motivation section and a smmary. Please notice the search bar at the top left if you want to quickly look for a topic (e.g. ‘marginalization’). Exercises from related SMASH courses have been included.

If you see any errors in this SOWISO class, want to ask questions, or have suggestions for improvements, please do this through the forum.

Floor Eijkelboom, Tin Hadži Veljković, and André Heck