ML Pipeline Creation

Build reproducible ML workflows whose inputs, outputs, lineage, and promotion criteria are explicit. Prefer the project's existing orchestrator and conventions; do not introduce a platform merely to demonstrate one.

Required Inputs

• Business objective and measurable model acceptance criteria
• Data sources, ownership, sensitivity, and expected refresh cadence
• Existing preprocessing, training, evaluation, and serving code
• Target environments and available orchestration or CI system
• Compute, cost, latency, reproducibility, and compliance constraints

If critical details are missing, state assumptions and design a platform-neutral pipeline before selecting an implementation.

Output Contract

Produce: