Workload:
180 h
|
Module Number INFO-4181 |
Module Title Pattern Recognition and Machine Learning |
Lecture Type(s) Lecture |
|---|---|---|
| ECTS | 6 | |
|
Work load - Contact time - Self study |
Workload:
180 h Class time:
60 h / 4 SWS Self study:
120 h |
|
| Duration | 1 Semester | |
| Frequency | Irregular | |
| Language of instruction | German and English | |
| Type of Exam | To be announced. |
|
| Content | The module covers the first chapters of the textbook by Ch. Bishop mentioned below: Introduction to Machine Learning, probability distributions, linear models for regression, linear models for classification, neural networks (short), kernel methods, mixture models and EM algorithms. |
|
| Objectives | Students acquire knowledge about machine learning on a modern statistical basis. They know mathematical-statistical approaches for solving pattern recognition problems and can apply them in exercises. |
|
| Allocation of credits / grading |
Type of Class
Status
SWS
Credits
Type of Exam
Exam duration
Evaluation
Calculation
of Module (%)
Lecture
V
o
2
4.0
wt
90
g
100
Tutorial
Ü
o
2
2.0
|
|
| Prerequisite for participation | There are no specific prerequisites. | |
| Lecturer / Other | Zell | |
| Literature | Ch. Bishop: Pattern Recognition and Machine Learning, Springer-Verlag; |
|
| Last offered | unknown | |
| Planned for | currently not planned | |
| Assigned Study Areas | INFO-INFO, INFO-PRAK, MEDI-APPL, MEDI-INFO, MEDI-MEDI, MEDI-VIS, ML-CS | |