Machine Learning is concerned with computer programs that automatically improve their performance through experience. This course covers the theory and practical algorithms for machine learning from a variety of perspectives. The 3-credit course covers introductory topics in the field of machine learning and data mining. Machine learning deals with computer algorithms for learning from many types of experience, ranging from fraud detection on credit card transactions, to robots learning to explore their environment, or to information-filtering for automatic recommendations. Topics include supervised learning, unsupervised learning and learning theory.

Short programming assignments include hands-on experiments with various learning algorithms.

Prerequisite: Calculus and Basic linear algebra. Statistics is recommended. Students should already have good programming skills, i.e. 2150 as prerequisite.