Machine learning algorithms are presented. Their use to build computational models are described.
- Advanced study course, 5 ECTS
- 12 lectures (24 h), Martti Juhola
- 5 weekly exercise times (10 h), Jyrki Rasku
- Additional scores: when one makes more of all weekly exercises than 30%, additional scores [0,5] are given as follows: ≥30% 0, ≥41% 1, ≥52% 2, ≥63% 3, ≥74% 4, ≥85% 5
- To pass the course: (1) at least 30% of weekly exercises have to be made and (2) the examination with scores of 12 or more from [0,30]
New! Matlab is used for exercises. Do this quickly (if not yet done):
To load Matlab you first need an activation code and obtaining this may take time. (You also need a UTA student account.) To be done via the following link:
Note the updated place of the first lecture!
On Tuesday the 6th March at 10-12, Pinni 1097.
On Tuesdays at 10-12 from the 13th March to the 17th April excluding the 3rd April, Pinni B3107
On Wednesdays at 10-12 from the 7th March to the 18th April excluding the 28 March, Pinni B3107
On Thursdays at 12-14 from the 22nd March to 26th April excluding the 29th March, Main building C6, but Linna K113 on the 26th April
On the 4th May (class D10a+b at 10-14) or the 31st May (class D10a+b at 16-20)