MachineLearning
Classical ML/MLOps — distinct from AI/ which is LLM/agentic-focused.
Why we need this / what value this brings
Distinct skillset and infra from LLM/agentic work (AI/) — relevant only once there's an actual predictive/classification use case.
When to use this
Once there's a concrete use case (ranking, fraud detection, recommendation) that a rules-based approach can't handle well.
How to use or implement this
Start with the simplest model that could plausibly work (or a heuristic) before reaching for anything sophisticated.
Subtopics
Research questions
- Does Localz have any actual ML use case yet (recommendation ranking, fraud detection) or is this purely background study?
Empty folder — drop notes, links, and findings here as you research.