| Detailed information |
| Original study plan |
Master's programme Computer Science 2025W |
| Learning Outcomes |
Competences |
| See lecture series by the same name.
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| Skills |
Knowledge |
| See lecture series by the same name.
|
See lecture series by the same name.
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| Criteria for evaluation |
Creativity and rigour in solving a complex machine learning project; clarity and systematicity of written project reports throughout the course of the project.
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| Methods |
Independent work on a complex machine learning problem by students / student groups, in several stages throughout the semester. Using public machine learning toolboxes, students go through all the stages of a pattern classification project of real-world complexity, from annotation, feature definition and extraction to the training of various classifiers and systematic experimentation. Joint discussion of ideas, experiments, and results. Presentations by lecturer and selected students or student groups.
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| Language |
English |
| Study material |
Lecture slides from the corresponding lecture course (VO). Additional information resources are provided if/when needed.
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| Changing subject? |
No |
| Further information |
This exercise course (UE) and the corresponding lecture series course (VO) form a didactic unit. The study results described here are achieved through the combination of these two courses.
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| Corresponding lecture |
in collaboration with 921PECOMLPV20: VL Machine Learning and Pattern Classification (3 ECTS) equivalent to
921PECOMLPK13: KV Machine Learning and Pattern Classification (4.5 ECTS)
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