Introduction to Machine Learning

Algorithms and machine learning
Advanced studies
Basic concepts and methods of machine learning, in theory and in practice. Supervised learning (classification, regression) and unsupervised learning (clustering). The course serves as preparation for various courses on data analysis, machine learning and bioinformatics. Course book: Course book: An Introduction to Statistical Learning with Applications in R, Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani, Springer, 2013.
Year Semester Date Period Language In charge
2009 autumn 04.11-11.12. 2-2 English


Time Room Lecturer Date
Wed 12-14 PHY D101 Hannes Wettig 04.11.2009-04.11.2009
Fri 12-14 CHE LS 1 Hannes Wettig 06.11.2009-27.11.2009
Wed 12-14 PHY E204 Hannes Wettig 11.11.2009-11.11.2009
Wed 12-14 PHY D101 Hannes Wettig 18.11.2009-09.12.2009
Fri 12-14 CK112 Hannes Wettig 04.12.2009-11.12.2009

Exercise groups

Group: 1
Time Room Instructor Date Observe
Tue 12-14 BK107 Matti Vuorinen 09.11.2009—11.12.2009
Group: 2
Time Room Instructor Date Observe
Mon 12-14 B119 Matti Vuorinen 09.11.2009—11.12.2009

Lectures on week 46 have been moved as follows: WED 11th 12-14 Physicum E204, FRI 13th 12-14 Chemicum LS1