- Data, feature extraction and PCA
- Measures of similarity, summary statistics and probabilities
- Probability densities and data visualization
- Decision trees and linear regression
- Overfitting, cross-validation and Nearest Neighbor
- Performance evaluation, Bayes, and Naive Bayes
- Artificial Neural Networks and Bias/Variance
- AUC and ensemble methods
- K-means and hierarchical clustering
- Mixture models and density estimation
- Association mining