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.


103-0849-00 GMultivariate Statistik und Machine Learning4 hrs
Thu08:50-11:30HIL D 53 »
K. Schindler

Catalogue data

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

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
In examination block forBachelor's Degree Programme in Geospatial Engineering 2018; Version 06.10.2021 (Examination Block 2)
ECTS credits4 credits
ExaminersK. Schindler
Typesession examination
Language of examinationGerman
RepetitionThe performance assessment is offered every session. Repetition possible without re-enrolling for the course unit.
Mode of examinationwritten 90 minutes
Additional information on mode of examinationDie Note setzt sich wie folgt zusammen: i) 90min schriftliche Prüfung und ii) obligatorisches Leistungselement in Form von Übungsaufgaben während des Semesters. Hinweis: Die Schlussnote setzt sich zu 70% aus der Prüfungsnote und zu 30% aus der Bewertung der Übungsaufgaben zusammen. Weder die Pruefung noch das obligatorische Leistungselement muessen für sich allein bestanden werden.
Written aidsNone
If the course unit is part of an examination block, the credits are allocated for the successful completion of the whole block.
This information can be updated until the beginning of the semester; information on the examination timetable is binding.

Learning materials

No public learning materials available.
Only public learning materials are listed.


No information on groups available.


Places40 at the most
PriorityRegistration for the course unit is until 21.02.2020 only possible for the primary target group
Primary target groupGeospatial Engineering BSc (107000)
Waiting listuntil 25.02.2020

Offered in

Geospatial Engineering BachelorExamination Block 2OInformation