scikit-learn Pipelines

Overview

A Pipeline chains preprocessing and the estimator into one object so that every fit happens on training folds only. This makes leakage structurally impossible and makes the model trivially serializable for serving. If you remember one thing from this pack: wrap preprocessing in a Pipeline.

When to use

• Any sklearn model with preprocessing (scaling, encoding, imputing).
• You need cross-validation that includes preprocessing.
• You want one artifact to save and serve.

Canonical pattern