Universität Wien
Warning! The directory is not yet complete and will be amended until the beginning of the term.

250014 VO Mathematical Methods of Data Analysis (2005W)

Mathematical Methods of Data Analysis

0.00 ECTS (4.00 SWS), SPL 25 - Mathematik

Details

Language: German

Lecturers

Classes (iCal) - next class is marked with N

  • Friday 07.10. 13:15 - 14:45 Seminarraum
  • Monday 10.10. 13:15 - 14:45 Seminarraum
  • Friday 14.10. 13:15 - 14:45 Seminarraum
  • Monday 17.10. 13:15 - 14:45 Seminarraum
  • Friday 21.10. 13:15 - 14:45 Seminarraum
  • Monday 24.10. 13:15 - 14:45 Seminarraum
  • Friday 28.10. 13:15 - 14:45 Seminarraum
  • Monday 31.10. 13:15 - 14:45 Seminarraum
  • Friday 04.11. 13:15 - 14:45 Seminarraum
  • Monday 07.11. 13:15 - 14:45 Seminarraum
  • Friday 11.11. 13:15 - 14:45 Seminarraum
  • Monday 14.11. 13:15 - 14:45 Seminarraum
  • Friday 18.11. 13:15 - 14:45 Seminarraum
  • Monday 21.11. 13:15 - 14:45 Seminarraum
  • Friday 25.11. 13:15 - 14:45 Seminarraum
  • Monday 28.11. 13:15 - 14:45 Seminarraum
  • Friday 02.12. 13:15 - 14:45 Seminarraum
  • Monday 05.12. 13:15 - 14:45 Seminarraum
  • Friday 09.12. 13:15 - 14:45 Seminarraum
  • Monday 12.12. 13:15 - 14:45 Seminarraum
  • Friday 16.12. 13:15 - 14:45 Seminarraum
  • Monday 09.01. 13:15 - 14:45 Seminarraum
  • Friday 13.01. 13:15 - 14:45 Seminarraum
  • Monday 16.01. 13:15 - 14:45 Seminarraum
  • Friday 20.01. 13:15 - 14:45 Seminarraum
  • Monday 23.01. 13:15 - 14:45 Seminarraum
  • Friday 27.01. 13:15 - 14:45 Seminarraum
  • Monday 30.01. 13:15 - 14:45 Seminarraum

Information

Aims, contents and method of the course

Topics:

1. Basic techniques; e.g., the least squares method,
regularization, covariance analysis, classification,
time series analysis, fast Fourier transform,
wavelets, neural networks, fuzzy logic

2. Application areas; e.g.,
artificial intelligence, pattern recognition,
image analysis, tomography,
protein folding, animal husbandry,
weather forecast, climate modeling,
high energy particle tracks, mathematical finance

The choice from these topics will partially depend on the
interests of the participants.

Assessment and permitted materials

Minimum requirements and assessment criteria

The goal is an understanding of basic method of modern data
analysis, leading to familiarity with and enabling to assess
concepts, techniques and algorithms for the analysis of large
data sets.

Examination topics

See topics

Reading list

Ein sehr empfehlenswertes Buch, das aber nur in Teilen der
Vorlesung entspricht, ist:

B.D. Ripley,
Pattern Recognition and Neural Networks,
Cambridge University Press, 1996.

Association in the course directory

Last modified: Mo 07.09.2020 15:40