Statistical Machine Learning
Summer Semester 2021
This course provides a more in-depth introduction into statistical methods in machine learning.
Course materials (Moodle) – TUCaN
|Event type||integrated course (IV4, 6CP, 4SWS), elective|
|Being taught||regularly, usually summer semesters|
|Time||Wednesdays, 13:30 – 17:00|
|First class||Wednesday, 21.04.2021|
|Location||online only (see Moodle)|
|Exam||written exam, details TBA|
- Statistical methods in machine learning
- Statistics, optimization, and linear algebra
- Bayesian decision theory
- Density estimation
- Non-parametric models
- Mixture models and the EM-algorithm
- Linear models for classification and regression
- Statistical learning theory
- Kernel methods for classification and regression
After successfully attending the course, students have developed a more in-depth understanding of statistical methods in machine learning.
Can be taken for credit toward BSc / MSc Informatik, MSc Visual Computing, MSc Autonome Systeme, BSc / MSc Computational Engineering and others. Students from other departments, e.g. Mathematik, Elektrotechnik, IST, or Physik are welcome, though academic credit may need to be arranged.
It is recommended to have taken Math classes from the bachelor's degree and to have basic programming abilities.