Introduction to Machine Learning
5
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.
Lectures
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
Time | Room | Instructor | Date | Observe |
---|---|---|---|---|
Tue 12-14 | BK107 | Matti Vuorinen | 09.11.2009—11.12.2009 |
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