machine_learning_course_basics

Use when creating a grounded, accessible, self-contained interactive learning experience from repository knowledge sources.

Use when creating an interactive review for an ML-course lecture and its course-specific source, safety, and publishing rules are needed.

Improve the ML course interactive textbook in the student repository. Use when adding or revising OKF concepts, learning paths, browser labs, textbook rendering, agent manifests, contribution guides, or public-safe course knowledge modules. Enforce source-grounded pedagogy, formula-level rigor when appropriate, OKF validation, rendered textbook checks, and consistency between descriptions, skills, learning objectives, indexes, and the agent manifest.

Helps a student navigate the ML course materials. Use when a student asks to find a lecture, set up their local environment, find example notebooks, or understand the interactive textbook. Guides the student to the correct commands (like `uv sync`) and paths without giving away practical answers.