Workload:
90 h
|
Module Number INF3159 |
Module Title Selected Topics in Machine Learning |
Type of Module Elective Compulsory |
|---|---|---|
| ECTS | 3 | |
|
Work load - Contact time - Self study |
Workload:
90 h Class time:
30 h / 2 SWS Self study:
60 h |
|
| Duration | 1 Semester | |
| Frequency | Irregular | |
| Language of instruction | German | |
| Type of Exam | Presentation and essay |
|
| Lecture type(s) | Proseminar | |
| Content | Special topics in machine learning, changing annually depending on the topicality of the topics, e.g. artificial neural networks, support vector machines, kernel methods, Gaussian processes, graphical models, Markov processes, kernel applications in chemoinformatics and bioinformatics, evolutionary algorithms. |
|
| Objectives | Students learned about specific topics in the field of machine learning. |
|
| Allocation of credits / grading |
Type of Class
Status
SWS
Credits
Type of Exam
Exam duration
Evaluation
Calculation
of Module (%) |
|
| Prerequisite for participation | There are no specific prerequisites. | |
| Lecturer / Other | Alle Dozenten | |
| Literature | Hängt von den aktuellen Themen ab und wird zur Verfügung gestellt |
|
| Last offered | - | |
| Planned for | - | |
| Assigned Study Areas | INFM1510, MEINFM1510 | |