Goals and Subjects

This class is intended to introduce you to the study of machine learning, both as it is currently understood and as it has developed over the past twenty years or so. We won't, unfortunately, have time to delve into a number of subjects in nearly as much depth as I would like, but we will attempt to introduce the key principles of ML and gain basic familiarity with the terminology, methodology, algorithms, and mathematical results. The goal is that, by the end of the course, you should know what techniques are available and how/when to apply them (or at least where to look to learn how), be prepared to read the literature independently, and, for graduate students, be ready to start engaging in research in the ML field. We'll be focusing on the statistical approach, which has emerged as the dominant viewpoint in the past ten years or so, though we'll also examine some symbolic and hybrid methods as time permits.