Marc Deisenroth travelled to Rwanda to teach statistics at the African Institute for Mathematical Sciences.
In the second installment of a two-part series, he talks about the masters course in Machine Intelligence that he taught, his experiences in teaching it, and his reflections more generally as his four-month sabbatical comes to an end.
During my time at AIMS, I taught a course on Foundations of Machine Learning, as part of the AMMI degree. The course covered mathematical foundations of machine learning and their application to (fairly basic) machine learning algorithms, such as linear regression or principal component analysis. The objective of this course was to uncover the intrinsic mathematical principles, which are often hidden in machine learning algorithms, to allow students to understand how and why these algorithms work and what their underlying assumptions are.