301169 SE Applied Machine Learning for biological problems (2019W)
- Registration is open from Th 05.09.2019 08:00 to Th 19.09.2019 18:00
- Deregistration possible until Th 19.09.2019 18:00
Classes (iCal) - next class is marked with N
Location: Seminar room 5.43 in the (former) University of Economics building, Augasse 2-6, Core A, 5th floor
Aims, contents and method of the course
Assessment and permitted materials
Group project/competition (25 pts.)
Bonus points are possible through additional activities (TBA)
Minimum requirements and assessment criteria
Attendance is encouraged, since concepts required for the exercises and the project are discussed in class, and we want the seminar to be interactive.
Participants must achieve at least 50 pts. by the end of the course.
< 50.0: 5
< 62.5: 4
< 75.0: 3
< 87.5: 2
else: 1Students need to bring their own laptop (we can provide a few, if required).
There are no strict prerequisites, but basic command line and Python skills are recommended.
Slides are and will be available online.
Bishop: Pattern recognition and machine learning (2006)
Hastie: The elements of statistical learning (2009)
Goodfellow: Deep learning (2016) (free online version: https://www.deeplearningbook.org/)Papers:
Relevant scientific literature will be introduced in the course.