End-to-end methodology for AI agents and software engineers to add machine learning algorithms to existing non-ML codeb…
End-to-end methodology for AI agents and software engineers to add machine learning algorithms to existing non-ML codebases. Covers problem framing, data readiness, architectural decoupling, and baseline model integration. Use when adding a machine learning capability to a codebase that has none, from problem framing through a baseline model. A reusable SKILL.md agent skill by affaan-m.
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