Theoretical Foundations of Machine Learning and Sequential Decision Making

(3 Credits)

Machine learning has become an indispensable part of many application areas, in science, engineering and business disciplines. But machine learning is not a single approach rather, it consists of a dazzling array of seemingly disparate frameworks and paradigms. This course aims to uncover the common foundational principles underlying this diverse array of techniques. The course has two components: offline learning (before the midterm) and online learning (after the midterm) and will provide students with a solid theoretical foundation in machine learning and allow them to start accessing the expanding literature in related topics.