Master's Computer Science Machine Learning 2

Summer semester 2021, Prof. Dr. Klaus-Robert Müller, Technische Universität Berlin

Content

1. Low-Dimensional Embedding (LLE)
2. Component Analysis 1 (CCA)
3. Component Analysis 2 (ICA)
4. Component Analysis 3 (Autoencoders)
5. Kernel Machines 1 (Structured Kernels)
6. Hidden Markov Models
7. Kernel Machines 2 (Structured Prediction)
8. Kernel Machines 3 (Anomaly Detection)
9. Deep Learning 1 (Structured Networks)
10. Deep Learning 2 (Structured Prediction)
11. Deep Learning 3 (Explainable AI)
12. Deep Learning 4 (Anomaly Detection)

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