Jan 11, 2026 — 12 min — Platform & AI
scikit-learn Pipelines That Survive Tuning and Deployment
Why tabular models drift between notebooks and production when preprocessing, sample metadata, hyperparameter search, and persistence are not treated as one scikit-learn pipeline contract.
Outcome: Defined a scikit-learn pipeline contract that keeps column preprocessing, metadata routing, hyperparameter search, evaluation, and deployment artifacts reproducible across dev, stage, and production.