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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.