Presentation.
Students learn about the mathematical theory that underlies modern machine learning systems in hands-on projects on a physical testbed/mini-lab. The seminar covers topics such as regression, conformal prediction, causal inference and time series analysis. The focus of this seminar is to highlight challenges that arise when theoretical foundations meet data collected from physical systems and how to deal with these challenges from both a theoretical and practical point of view. Students conduct multiple mini-projects regarding each concept and present one these projects for grading.
