Machine Learning for Pattern Recognition / Mønstergenkendelse

On this course we will use KU's new learning management system Absalon.

You can login to Absalon through your punkt.ku account. After login at punkt.ku select Absalon from the menu. If you are registered for the course, it will appear in your list of courses. Select the course to see detailed information about the course.

-- Kim Steenstrup Pedersen

This is a tentative lecture and exercise plan (see Absalon for up to date information):

Weekly Schedule:

Monday 13:15 - 16:00, lectures

Thursday 9:15 - 12:00, lectures

Thursday 13:00 - 16:00, exercises

Tuesday 10/6: 9:15 - 12:00, lectures, 13:00 - 16:00, exercises

Lecture rooms:

Monday 13:15 - 16:00, DIKU N037

Thursday 9:15 - 12:00, HCØ Aud. 3

Thursday 13:00 - 16:00, DIKU S125

Tuesday 10/6: 9:15 - 12:00, DIKU N004, 13:00 - 16:00, DIKU S125

Lecture	Date	Lecturer	Title	Material
1	Mon. 21/4	KSP	Introduction	CB ch. 1
2	Thur. 24/4	KSP	Bayesian statistics	CB ch. 2
3	Mon. 28/4	KSP	Linear models of regression, part 1	CB ch. 3
4	Mon. 5/5	KSP	Linear models of regression, part 2	CB ch. 3
5	Thur. 8/5	OW	Classification, part 1	CB ch. 4
6	Thur. 15/5	OW	Classification, part 2	CB ch. 4
7	Mon. 19/5	AK	Neural networks, part 1	CB ch. 5
8	Thur. 22/5	AK	Neural networks, part 2	CB ch. 5
9	Mon. 26/5	OW	Kernel methods, SVM	CB ch. 6, 7
10	Thur. 29/5	OW	PCA	CB ch. 12
11	Mon. 2/6	OW	Mixture models, part 1	CB ch. 9
12	Mon. 9/6	OW	Mixture models, part 2	CB ch. 9
13	Tues. 10/6	TH	Graphical models, part 1	CB ch. 8
14	Thur. 12/6	TH, KSP	Graphical models, part 2 Course evaluation	CB ch. 8

CB: C. Bishop, Pattern Recognition and Machine Learning

Exercise	Date	Lecturer	Title
1	Thur. 24/4	KSP	Matlab and probability distributions
2	Thur. 8/5	KSP	Linear regression
3	Thur. 15/5	OW	Classification
4	Thur. 22/5	AK	Neural networks
5	Thur. 29/5	OW	Kernel methods / PCA
6	Tues. 10/6	OW	Mixture models
7	Thur. 12/6	TH	Graphical models