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learning-systems

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A structured skill for AI coding agents to design, review and diagnose robust machine learning systems — from baseline to production. Covers supervised learning, imitation, offline RL, online RL, self-play, and hybrid strategies. Includes reward design, curriculum, experimental governance, reproducibility, observability, safety, deployment, and rol

  • Updated Jun 19, 2026
  • Python

Learning-Native Adaptive Software Framework (LNASF) — a technical architecture for reusable software components that learn from runtime experience and adapt while retaining deterministic fallback behavior.

  • Updated Aug 28, 2026
  • TeX

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