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.
Exam
11.12.2013
09.00
B123
| Year | Semester | Date | Period | Language | In charge |
|---|---|---|---|---|---|
| 2013 | autumn | 29.10-06.12. | 2-2 | English | Jyrki Kivinen |
Lectures
| Time | Room | Lecturer | Date |
|---|---|---|---|
| Tue 10-12 | D122 | Jyrki Kivinen | 29.10.2013-06.12.2013 |
| Fri 10-12 | D122 | Jyrki Kivinen | 29.10.2013-06.12.2013 |
| Mon 12-14 | C220 | Jyrki Kivinen | 09.12.2013-09.12.2013 |
Exercise groups
| Time | Room | Instructor | Date | Observe |
|---|---|---|---|---|
| Fri 14-16 | B222 | Yuan Zou | 04.11.2013—06.12.2013 |
On Tuesday 19th of November the lecture is moved to room B222!
Registration for this course starts on Tuesday October 8th at 9.00. There is additional guidance for Matlab/R on Tue October 29th at 12-14 in B221 and Fri November 1st at 12-14 in B221.
Information for international students
The course will be taught in English. All materials will appear on the English version of this page.
Announcements
- The course has been graded. The course results are available in the department intranet.
- Please fill in a feedback form for the course!
- Details of the programming assignment for separate examinations are now available in the Examinations tab.
General
Kurssin opetuskieli on englanti. Tarkemmat tiedot tulevat tämän sivun englanninkieliseen versioon.