Random Forest
Random Forest in the context of production machine-learning systems.
Lessons
Formal explanations, examples, simulations, and checkpoints.
Trees as learned decision rules
Use trees as learned decision rules to move the trees & boosting production brief toward a defensible release.
Trees, forests & gradient boostingRandom forests and diversity
Use random forests and diversity to move the trees & boosting production brief toward a defensible release.
Trees, forests & gradient boostingGradient boosting as error correction
Use gradient boosting as error correction to move the trees & boosting production brief toward a defensible release.
Trees, forests & gradient boostingXGBoost: regularized boosting at scale
Use xgboost: regularized boosting at scale to move the trees & boosting production brief toward a defensible release.
Trees, forests & gradient boostingCalibrating and explaining ensembles
Use calibrating and explaining ensembles to move the trees & boosting production brief toward a defensible release.
Courses & assignments
Dependency-authoritative learning units.
Casebook
Reported facts and course reconstructions.