Master's Computer Science Machine Learning 1

Winter semester 2021/22, Prof. Dr. Klaus-Robert Müller, Technische Universität Berlin

Content

1. Bayes Decision Theory
2. Parameter Estimation
3. Principal Component Analysis
4. Fisher Discriminant
5. Model Selection
6. Neural Networks 1
7. Learning Theory & Kernels
8. Support Vector Machines
9. Kernel Ridge Regression
10. Boosting
11. Decision Trees and Random Forests
12. Neural Networks 2
13. Latent Variable Models / Clustering
14. Explainable AI

Exercise solutions are based on my own work, the work of my homework group, or the class sample solutions.