After successful completion of the course, students are able to scientifically work on topics from machine learning and its applications in insurance mathematics and to present the learning outcomes on the blackboard or via slides.
Generalised linear models, generalised additive models, credibility in insurance, neural networks, regression trees, random forest, telematics etc.
Presentation by students (slides or blackboard), handout for all participants, a detailed written summary for the organisers.
Please note:
Presentation, seminar paper and participation