Inhalt

[ INMAWUETCML ] UE Theoretical Concepts of Machine Learning

Versionsauswahl
Workload Education level Study areas Responsible person Hours per week Coordinating university
1,5 ECTS M2 - Master's programme 2. year Computer Science Sepp Hochreiter 1 hpw Johannes Kepler University Linz
Detailed information
Original study plan Master's programme Computer Science 2013W
Objectives This practical course complements the lecture "Theoretical Concepts of Machine Learning" and aims at practicing the concepts and methods acquired in the lecture.
Subject
  • Generalization error
  • Bias-variance decomposition
  • Error models
  • Model comparisons
  • Estimation theory
  • Statistical learning theory
  • Worst-case and average bounds on the generalization error
  • Structural risk minimization
  • Bayes framework
  • Evidence framework for hyperparameter optimization
  • Optimization techniques
  • Theory of kernel methods
Criteria for evaluation Marking is based on homework
Methods Students are given assignments in 1-2 week intervals. Homework must be handed. Results are to be presented and discussed in the course.
Language English
Study material Assignments and homework submissions are managed via JKU Moodle. Where necessary, complimentary course material is provided for download.
Changing subject? Yes
On-site course
Maximum number of participants -
Assignment procedure Direct assignment