1. Einführung
  2. Lineare Regression
  3. Logistische Regression
  4. Multinomial Classification
  5. Feature Engineering
  6. Bias & Variance
  7. Decision Trees & Ensemble Models
  8. Support Vector Machines
  9. Clustering