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News

• 26/2 Added list of activities (here)
• 15/1 Homepage created.

Course Coordinator

Erik Lindström, tel 046-222 45 78, , MH:129.

General information

University credits: 7.5

Lectures:

Lecturer	Day	Chapter	Exercises
Erik Lindström	14/1 M	1 Introduction 2 Overview of Superv. Learning	2.2, 2.6
Martin Byröd	21/1 M	3 Lin. meth. for regression	3.3, 3.11
Susann Stjernqvist	24/1 T	4 Lin. meth. for classification	4.2 a-c, 4.5
David Bolin	28/1 M	5 Basis expansion and regularization	5.1, 5.7
Jakob Sternby	31/1 T	6 Kernel methods	6.3, 6.8
Mats Brodén	4/2 M	7 Model assessment and selection	7.1, 7.4
Jonas Ströjby	7/2 T	8 Model Inference and averaging	8.2, 8.4
Johan Sandberg	11/2 M	9 Additive models and trees	9.1, 9.3 or 9.7b
Johannes Sivén	18/2 M	10 Boosting and additive trees	10.5
Johan Lindström	25/2 M	13 Prototype methods	13.1, 13.7
Charlotte Soneson	3/3 M	12 Support Vector Machines	12.1, 12.10
Jörg Wegener	10/3 M	11 Neural networks	11.1, 11.2
Olof Enqvist	17/3 M	14 Unsupervised learning	14.3, valfri

List of activities can be found here.

Literature

The Elements of Statistical Learning, Hastie, Tibshirani and Friedman (2001). Springer-Verlag. 536 pages, see also the book homepage

Assessment

Active participation in the course as discussed during the course.