103-0849-00L  Multivariate Statistics and Machine Learning

SemesterSpring Semester 2020
LecturersK. Schindler
Periodicityyearly recurring course
Language of instructionGerman
CommentNumber of participants limited to 40.

AbstractIntroduction to statistical modelling and machine learning.
ObjectiveThe goal is to familiarise students with the principles and tools of machine learning, and to enable them to apply them for practical data analysis.
Contentmultivariate probability distributions; comparison of distributions; regression; classification; model selection and cross-validation; clustering and density estimation; mixture models; neural networks
LiteratureC. 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