Mle Workflow

This is the skill you want when a notebook needs to become a production ML system. It walks you through data contracts, reproducible training, evaluation gates, deployment, monitoring, and rollback without forcing one architecture onto every problem. The scope calibration is refreshingly honest: it tells you not to add heavyweight MLOps machinery when a baseline, eval script, and rollback note would be enough. What makes it useful is the table mapping standard SWE workflows to ML contexts, so you reuse existing surfaces like TDD, code review, database migrations, and canary rollout instead of building a parallel stack. Good for ranking systems, classifiers, recommenders, forecasting pipelines, and anything that needs to survive contact with production data drift.

Install to Claude Code

npx -y skills add affaan-m/ecc --skill mle-workflow --agent claude-code