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Die folgenden Informationen sind noch nicht freigegeben und deshalb unverbindlich: Statistical Machine Learning SemesterWiSe 2026 / 27 Lecturer Merle Behr Type of course (Veranstaltungsart) Vorlesung German title Statistisches Maschinelles Lernen Contents This course covers the mathematical and statistical foundations of machine learning (ML). It presents theoretical and statistical analysis tools for studying ML methods, applied to nearest-neighbor methods, random forests, and neural networks, alongside an introduction to statistical learning theory. Literature The course will be based on various material, including journal articles. Important references for the course are - Luc Devroye, Laszlo Gyorfi, and Gabor Lugosi. A Probabilistic Theory of Pattern Recognition, volume 31 of Stochastic Modelling and Applied Probability. Springer New York, New York, NY, 1996. - Laszlo Gyorfi, Michael Kohler, Adam Krzyzak, and Harro Walk. A Distribution-Free Theory of Nonparametric Regression. Springer Series in Statistics. Springer New York, New York, NY, 2002. Recommended previous knowledge Linear algebra, analysis, and probability theory. Time/Date The course only starts on December 2nd!! Lectures: Wednesdays 2 - 4pm and Thursdays 12 - 2 pm; Tutorial: Fridays 10 - 2pm Location Bajuwarenstrasse 4 (FIDS) Course homepage SPUR: Statistical Machine Learning (DAT-M-MLS-SML); 70360a and 70360b (Disclaimer: Dieser Link wurde automatisch erzeugt und ist evtl. extern) Registration
MV ECTS 6 |