Machine learning is ubiquitous in modern science. Its mathematical foundations lie at the intersection of optimization/optimal control, approximation theory, and statistics. To shed some light on this interplay, in this seminar we study several aspects and methods of Machine Learning from both numerical and statistical perspectives. The seminar is jointly organized by Martin Frank (SCC), Sebastian Krumscheid (SCC) and Mathias Trabs (STOCH).