Introduction to Supervised Learning

Harvard FAS

This course will dive into the statistical properties of various machine learning methods that arise in supervised problems. The goal of the course is to introduce and prepare students for theoretical and methodological research in statistical machine learning. Topics we will discuss include nearest neighbors, no free lunch theorems, curse of dimensionality, structured learning, subset selection, shrinkage methods, principal components regression, double descent, implicit regularization…