The lecture will be held as inverted classroom with lecture videos and one weekly in-presence session. The tutorials will be held in presence (when possible); they begin in the 2nd week. Details are discussed in the kickoff lecture (Thursday, Sep 8, 12:00).
Machine learning is concerned with building computer systems that improve with experience as well as the study of learning processes, including the design of algorithms that are able to make predictions or extract knowledge from data. The aim of this module is to provide an introduction into the field of machine learning, and study algorithms, underlying concepts, and theoretical principles.
More advanced topics are covered in the follow up course “IE 678 Deep Learning”.
Lecture recordings, lecture notes, exercises, assignments, and supplementary material can be found in ILIAS.