algorithm:pca

PCA

PCA in the context of production machine-learning systems.

Lessons

Formal explanations, examples, simulations, and checkpoints.

Use pca and representation geometry to move the unsupervised & retrieval production brief toward a defensible release.

Use clustering as an operational hypothesis to move the unsupervised & retrieval production brief toward a defensible release.

Use density clusters and novel anomalies to move the unsupervised & retrieval production brief toward a defensible release.

Use embeddings and similarity to move the unsupervised & retrieval production brief toward a defensible release.

Use approximate retrieval under latency to move the unsupervised & retrieval production brief toward a defensible release.

Dependency-authoritative learning units.

A PCA, clustering, anomaly, and nearest-neighbor retrieval investigation.

Assignment: Incident discovery and retrieval system

Reported facts and course reconstructions.