Universität Wien
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040649 UK Machine Learning (2019W)

4.00 ECTS (2.00 SWS), SPL 4 - Wirtschaftswissenschaften
Continuous assessment of course work
Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 30 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Thursday 03.10. 16:45 - 18:15 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 10.10. 16:45 - 18:15 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 17.10. 16:45 - 18:15 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 24.10. 16:45 - 18:15 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 31.10. 16:45 - 18:15 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 07.11. 16:45 - 18:15 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 14.11. 16:45 - 18:15 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 21.11. 16:45 - 18:15 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 28.11. 16:45 - 18:15 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 05.12. 16:45 - 18:15 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 12.12. 16:45 - 18:15 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 09.01. 16:45 - 18:15 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 16.01. 16:45 - 18:15 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 23.01. 16:45 - 18:15 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock
  • Thursday 30.01. 16:45 - 18:15 Hörsaal 10 Oskar-Morgenstern-Platz 1 2.Stock

Information

Aims, contents and method of the course

Basic knowledge about machine learning

Contents:
- Recursive estimation and stochastic gradient methods
- Linear classifier and support vector machines
- Neural Networks
- Bayesian Networks
- Clustering and the EM-Algorithm
- Hidden Merkur Models - Baum/Welch and Viterbi-Algorithms

Assessment and permitted materials

Solving problems taken from the following book: Bishop, Christopher M. (2006). Pattern Recognition and Machine Learning. Springer.

Minimum requirements and assessment criteria

Examination topics

All topics covered in class.

Reading list

Bishop, Christopher M. (2006). Pattern Recognition and Machine Learning. Springer.

Association in the course directory

Last modified: Mo 07.09.2020 15:19