Build ML Pipeline

Declare a skrub DataOps graph, then attach the locked splitter and any non-default score. Smoke is the last step here. Do not fit, tune, persist, or call skore.evaluate.

Human-facing prose

Details: setup-workspace references/human_facing_prose.md. Experiment markdown, design-note Method text, and # comments describe this pipeline. Questions and the checkpoint use the same data-science language: not skill ids, G-* names, or the wrapper CLI. <!-- results-embed: … --> is a site marker. Authoring hints stay in this skill.

X marker is .skb.mark_as_X(). Predict grid is the rows to score. Cross-row step reads other rows (lag, rolling, group-agg, side join). Layers 1 / 2 / 3 are sources, the grid plus marker, and features after the marker.