Clustering, dimensionality reduction, and anomaly detection.
K-means, hierarchical clustering, DBSCAN, choosing K, and failure cases.
PCA, eigenvalue intuition, explained variance, and when PCA fails.
Anomaly detection, distance metrics, and high-dimensional effects.