183.605 Machine Learning for Visual Computing
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2017W, VU, 3.0h, 4.5EC
TUWEL

Properties

  • Semester hours: 3.0
  • Credits: 4.5
  • Type: VU Lecture and Exercise

Aim of course

Understanding of principles of machine learning. Application of machine learning methods to visual computing.

Subject of course

- linear models for regression and classification (Perceptron, Linear Basis Function Models, RBF, historical overview), applications in computer vision

- neural nets

- error functions and optimization (e.g., pseudo-inverse, gradient descent, newton method)

- model complexity, regularization, model selection, VC dimension 

- kernel methods: duality, sparsity, Support Vector Machine

- principal component analysis and Hebbian rule, canonical correlation analysis

- bayesian view of the above models, bayesian regression, relevance vector machine

- clustering und vektor quantisierung (e.g., k-means)

- Overview of deep learning models 

 

Additional information

ECTS Breakdown:

4.5 ECTS = 112.5 hours
30     lecture time
70     2 assignments (including studying machine learning principles, 
       reading documents and literature, 
implementation of MATLAB code and writing documentation)
2.5    2 interviews (including preparation time)

Lecturers

Institute

Course dates

DayTimeDateLocationDescription
Tue12:00 - 14:0003.10.2017 - 23.01.2018EI 8 Pötzl HS - QUER Lecture MLVC 183.605
Tue12:00 - 14:0003.10.2017EI 8 Pötzl HS - QUER Presentation and first lecture
Machine Learning for Visual Computing - Single appointments
DayDateTimeLocationDescription
Tue03.10.201712:00 - 14:00EI 8 Pötzl HS - QUER Lecture MLVC 183.605
Tue03.10.201712:00 - 14:00EI 8 Pötzl HS - QUER Presentation and first lecture
Tue10.10.201712:00 - 14:00EI 8 Pötzl HS - QUER Lecture MLVC 183.605
Tue17.10.201712:00 - 14:00EI 8 Pötzl HS - QUER Lecture MLVC 183.605
Tue24.10.201712:00 - 14:00EI 8 Pötzl HS - QUER Lecture MLVC 183.605
Tue31.10.201712:00 - 14:00EI 8 Pötzl HS - QUER Lecture MLVC 183.605
Tue07.11.201712:00 - 14:00EI 8 Pötzl HS - QUER Lecture MLVC 183.605
Tue14.11.201712:00 - 14:00EI 8 Pötzl HS - QUER Lecture MLVC 183.605
Tue21.11.201712:00 - 14:00EI 8 Pötzl HS - QUER Lecture MLVC 183.605
Tue28.11.201712:00 - 14:00EI 8 Pötzl HS - QUER Lecture MLVC 183.605
Tue05.12.201712:00 - 14:00EI 8 Pötzl HS - QUER Lecture MLVC 183.605
Tue12.12.201712:00 - 14:00EI 8 Pötzl HS - QUER Lecture MLVC 183.605
Tue19.12.201712:00 - 14:00EI 8 Pötzl HS - QUER Lecture MLVC 183.605
Tue09.01.201812:00 - 14:00EI 8 Pötzl HS - QUER Lecture MLVC 183.605
Tue16.01.201812:00 - 14:00EI 8 Pötzl HS - QUER Lecture MLVC 183.605
Tue23.01.201812:00 - 14:00EI 8 Pötzl HS - QUER Lecture MLVC 183.605

Course registration

Begin End Deregistration end
25.09.2017 09:00 11.10.2017 23:59 11.10.2017 23:59

Registration modalities

Please register for the course in TISS. After registration you can team up as a group of 3 students in TUWEL.

Curricula

Study CodeObligationSemesterPrecon.Info
066 453 Biomedical Engineering Not specified
066 932 Visual Computing Mandatory elective
066 935 Media Informatics Mandatory elective
066 936 Medical Informatics Mandatory elective
066 950 Didactic for Informatics Mandatory elective

Literature

No lecture notes are available.

Continuative courses

Miscellaneous

Language

German