Tabular
Tabular in the context of production machine-learning systems.
Lessons
Formal explanations, examples, simulations, and checkpoints.
Linear regression as a production baseline
Use linear regression as a production baseline to move the classical baselines production brief toward a defensible release.
Linear, probabilistic, neighbor & margin modelsLogistic regression, odds, and calibration
Use logistic regression, odds, and calibration to move the classical baselines production brief toward a defensible release.
Linear, probabilistic, neighbor & margin modelsNaive Bayes under sparse data
Use naive bayes under sparse data to move the classical baselines production brief toward a defensible release.
Linear, probabilistic, neighbor & margin modelskNN, distance, and local decisions
Use knn, distance, and local decisions to move the classical baselines production brief toward a defensible release.
Linear, probabilistic, neighbor & margin modelsSVMs, margins, and kernels
Use svms, margins, and kernels to move the classical baselines production brief toward a defensible release.
Courses & assignments
Dependency-authoritative learning units.
Casebook
Reported facts and course reconstructions.