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300169 SE Applied Machine Learning for biological problems (2017S)

5.00 ECTS (3.00 SWS), SPL 30 - Biologie
Continuous assessment of course work

Details

max. 20 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

Starting at Friday 10.3.2017, 14:00 o'clock in Konferenzraum Ökologie, UZA I, Althanstrasse 14.

Friday 10.03. 14:00 - 18:00 EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Konferenzraum Ökologie Biozentrum 2.241 1.OG
Friday 17.03. 14:00 - 18:00 EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Konferenzraum Ökologie Biozentrum 2.241 1.OG
Friday 24.03. 14:00 - 18:00 EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Konferenzraum Ökologie Biozentrum 2.241 1.OG
Friday 31.03. 14:00 - 18:00 EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Konferenzraum Ökologie Biozentrum 2.241 1.OG
Friday 07.04. 14:00 - 18:00 EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Konferenzraum Ökologie Biozentrum 2.241 1.OG
Friday 28.04. 14:00 - 18:00 EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Konferenzraum Ökologie Biozentrum 2.241 1.OG
Friday 05.05. 14:00 - 18:00 EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Konferenzraum Ökologie Biozentrum 2.241 1.OG
Friday 12.05. 14:00 - 18:00 EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Konferenzraum Ökologie Biozentrum 2.241 1.OG
Friday 19.05. 14:00 - 18:00 EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Konferenzraum Ökologie Biozentrum 2.241 1.OG
Friday 26.05. 14:00 - 18:00 EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Konferenzraum Ökologie Biozentrum 2.241 1.OG
Friday 02.06. 14:00 - 18:00 EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Konferenzraum Ökologie Biozentrum 2.241 1.OG
Friday 09.06. 14:00 - 18:00 EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Konferenzraum Ökologie Biozentrum 2.241 1.OG
Friday 16.06. 14:00 - 18:00 EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Konferenzraum Ökologie Biozentrum 2.241 1.OG
Friday 23.06. 14:00 - 18:00 EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Konferenzraum Ökologie Biozentrum 2.241 1.OG
Friday 30.06. 14:00 - 18:00 EDV-Raum 2 Ökologie Biozentrum Z1.023 EG
Konferenzraum Ökologie Biozentrum 2.241 1.OG

Information

Aims, contents and method of the course

After the course, the participants should be able to see if something is a problem for machine learning or not, given a particular question and data.
And also to solve it, at least if it is a kind of plain problem of this type.

machine learning methods introduced/used in the course:
tree learner
SVMs
perceptron/NNs
frequent itemset miners
metalearner

Assessment and permitted materials

There will be exercises and 3 small multiple choice tests.

Minimum requirements and assessment criteria

Half of the exercises must be done (halfway correct).
The final grade is formed from the 3 multiple choice tests.
Attendance is not so strict, as long as exercises and tests are done.
There might be one additional test if somebody misses one;

Examination topics

Everything presented in the course.
Slides are and will be available online.

Reading list


Association in the course directory

MMEI II-1.2, MMEI II-2.2, MMB W-2, MMB W-3, PIK 2

Last modified: Fr 31.08.2018 08:56