Contemporary machine learning sits at the intersection of three major branches of mathematics: linear algebra, calculus, and probability.

Today I released the third and final video in my Math for Machine Learning series, which covers core intuitions needed for ML from each of these three toolkits, with an emphasis on the programmers’ perspective. It also includes interactively-graded exercises.

Check the videos out here. Comment on them and let me know what you think!