Module CS5450 T
Module part: Machine Learning (MaschLerna)
Duration
1 Semester
Turnus of offer
each winter semester
Credit points
4
Course of studies, specific fields and terms:
- Master Biophysics 2023, module part, advanced curriculum
- Master Computer Science 2019, module part, Module part
- Master MES 2020, module part, computer science / electrical engineering
- Master Entrepreneurship in Digital Technologies 2020, module part, Module part
- Master Biophysics 2019, module part, advanced curriculum
- Master IT-Security 2019, module part, Module part
- Master Entrepreneurship in Digital Technologies 2014, module part, Module part
- Master MES 2014, module part, computer science / electrical engineering
- Master Computer Science 2014, module part, Module part
Classes and lectures:
- Machine Learning (exercise, 1 SWS)
- Machine Learning (lecture, 2 SWS)
Workload:
- 20 hours exam preparation
- 55 hours private studies
- 45 hours in-classroom work
Contents of teaching:
- Representation learning, including manifold learning
- Statistical learning theory
- VC dimension and support vector machines
- Boosting
- Deep learning
- Limits of induction and importance of data ponderation
Qualification-goals/Competencies:
- Students can understand and explain various machine-learning problems.
- They can explain and apply different machine learning methods and algorithms.
- They can chose and then evaluate an appropriate method for a particular learning problem.
- They can understand and explain the limits of automatic data analysis.
Grading through:
- exam type depends on main module
Responsible for this module:
- Siehe Hauptmodul
Literature:
- Chris Bishop : Pattern Recognition and Machine Learning Springer ISBN 0-387-31073-8
- Vladimir Vapnik : Statistical Learning Theory Wiley-Interscience, ISBN 0471030031
- Tom Mitchell : Machine Learning McGraw Hill. ISBN 0-07-042807-7
Language:
- English, except in case of only German-speaking participants
Notes:
Admission requirements for taking the module:- None
Admission requirements for participation in module examination(s):
- Successful completion of exercise assignments as specified at the beginning of the semester.
Module Exam(s):
- CS5450-L1: Machine Learning, oral exam, 100% of module grade.
(Is part of the module CS4290, CS4511, CS5400, CS4251-KP08)
Last Updated:
13.09.2021