algorithm:pca
PCA
PCA in the context of production machine-learning systems.
Lessons
Formal explanations, examples, simulations, and checkpoints.
Unsupervised learning, anomalies & retrieval
PCA and representation geometry
PCA preserves dominant geometric variation, not automatically the information your decision needs.
Unsupervised learning, anomalies & retrievalClustering as an operational hypothesis
A cluster becomes knowledge only when stable geometry connects to a repeatable human or system action.
Unsupervised learning, anomalies & retrievalDensity clusters and novel anomalies
Density methods flag what is locally disconnected; people and outcomes determine what is truly novel and important.
Unsupervised learning, anomalies & retrievalEmbeddings and similarity
Similarity is a modeling choice: the same vectors tell different stories under cosine and dot product.
Unsupervised learning, anomalies & retrievalApproximate retrieval under latency
Approximate retrieval is an explicit recall–latency contract, not a transparent substitute for exact search.
Courses & assignments
Dependency-authoritative learning units.
Casebook
Reported facts and course reconstructions.