103-0849-00L Multivariate Statistics and Machine Learning
| Semester | Spring Semester 2021 |
| Lecturers | K. Schindler |
| Periodicity | yearly recurring course |
| Language of instruction | German |
| Comment | Number of participants limited to 40. |
| Abstract | Introduction to statistical modelling and machine learning. |
| Learning objective | The goal is to familiarise students with the principles and tools of machine learning, and to enable them to apply them for practical data analysis. |
| Content | multivariate probability distributions; comparison of distributions; regression; classification; model selection and cross-validation; clustering and density estimation; mixture models; neural networks |
| Literature | C. Bishop: Pattern Recognition and Machine Learning, Springer 2006 T. Hastie, R. Tibshirani, J. Friedman, The Elements of Statistical Learning, Springer 2017 R. Duda, P. Hart, D. Stork: Pattern Classification, Wiley 2000 |