ML Case Labs — Validation, Boosting, Segmentation, Pipelines
P2 applied-ML labs (~40 h with course 18): regularized regression + leakage-controlled CV, RF vs boosting with calibration/thresholds, clustering + business readouts, sklearn pipelines + SHAP, closing in two capstones (campaign classifier, churn-ML with SHAP story).
10 weeks
4 modules, 20 lessons
0
~23 hours
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Course Curriculum
M1 — Regularized Regression + Validation DisciplineFREE PREVIEW
Ridge/lasso case, GroupKFold leakage lab, validation quiz, CV notebook + leakage-audit submissions.
M2 — Boosting + Calibrated EvaluationFREE PREVIEW
RF vs XGB/LGBM case, PR-AUC/Brier/threshold article, boosting quiz, campaign classifier + error-slice submissions.
M3 — Clustering + Pipelines/SHAPFREE PREVIEW
Clustering lab video, segmentation readout article, unsupervised quiz, readout + pipeline submissions.
M4 — Pipelines Explainability + CapstonesFREE PREVIEW
Pipeline/SHAP walkthrough, explainability quiz, 25Q module test, campaign + churn capstones.
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