Göm meny

Machine Learning


Lectures

Each lecture comes with a list of recommended problems to be solved as shown in the table below. If there are no letters in front of the numbers, they refer to problems in the book by Bishop. If the letters HTF appears in front of the number that means that exercise is to be found in the book by Hastie, Tibshirani and Friedman.

Note that the slides provided below only covers a small part of the lectures, the whiteboard is used quite extensively.

Nr. Date Contents (Instructor) Pres.
1 May 25 (9-12) Introduction, Linear Regression (intro)
(Chap. 1-3.2, notes [pdf])
Problems: 2.13, 2.29, 2.32, 2.34, 2.40, 2.44, 2.47, 1.25, 1.26, 3.8
Le1
2 May 26 (9-12) Linear regression, Linear Classification
(Chap. 3.3-3.6, Chap. 4, HTF Chap. 3)
Problems: 3.9, 3.12, 3.13, 4.5, 4.19, 4.25, HTF:2.8
Le2
3 May 27 (8-11) Expectation Maximization and Clustering (Notes [pdf], Chap. 9)
Problems: 9.8, 9.9, 9.11, 12.24 (also in Matlab, see lecture 1)
Le3
4 June 7 (9-12) Neural Networks, Gaussian Processes
(Chap. 5-6)
Problems: 5.4, 5.16, 6.3, HTF: 11.5 and here
Le4
5 June 8 (9-12)
Support Vector Machines and Approximate Inference (Chap. 7, 10, code1, notes [pdf], and code2)
Problems: [svm], 10.4, 10.7, 10.26, 10.38.
Le5
6 June 9 (9-12) Boosting, Graphical Models (brief)
(Chap. 14.3, Chap. 8.1-8.2)
Problems: 14.6, 14.7, 8.1, 8.3, 8.4, 8.7
Le6
7 June 10 (9-12) MCMC and Sampling Methods
(Chap. 11)
Problems: Available here, m-file
Le7
Thomas Schön

Associate Professor in Automatic Control

Phone:
+46 13 281373
Mobile (private):
+46 735 933 887
E-mail:
schon_at_isy.liu.se
Address:
Dept. of Electrical Engineering
Linköping University
SE-581 83 Linköping
Sweden
Visiting Address:
Campus Valla
Building B
Room 2A:NNN (in the A corridor on the ground floor between entrance 25 and 27)


Informationsansvarig: Thomas Schön
Senast uppdaterad: 2012-10-13