mlops-patterns

github:colingwuyu/optaic-trading · first committed 2026-01-01 · source · badge

Follow these patterns when implementing MLOps features in OptAIC. Use for ML model definitions (5-component structure), model instances, training/inference pipelines, model registry, and monitoring. Covers signal models, macro regime models, relevance models, and signal combining/filtering models.

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Listed, not yet scored. This skill has no public model test yet. It is in the scoring queue; submitted skills go first, then the most-installed.

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1 commit to this file on GitHub (newest first).

2026-01-01 · commit a46e150 · feat: Introduce MLOps architecture, unified ML SDK design, and related Claude skill documentation.

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