Execute this skill empowers AI assistant to construct recommendation systems using collaborative filtering, content-based filtering, or hybrid approaches. it analyzes user preferences, item features, and interaction data to generate personalized recommendations... Use when appropriate context detected. Trigger with relevant phrases based on skill purpose.
5.8
Rating
0
Installs
Machine Learning
Category
This skill provides a solid foundation for building recommendation systems with clear examples and referenced implementation scripts. The description covers collaborative, content-based, and hybrid filtering approaches with concrete use cases. Task knowledge is strong given the referenced Python scripts for data preprocessing, collaborative filtering, content-based filtering, and evaluation. Structure is good with a logical SKILL.md overview and separate implementation files. However, descriptionCoverage could be more specific about required inputs (data formats, parameters) and expected outputs. Novelty is moderate - while recommendation systems involve complexity, the skill appears to wrap standard ML workflows (data prep, training, evaluation) that a capable CLI agent could potentially handle with sufficient prompting, though the automation and best practices integration do provide value in reducing token usage and ensuring proper implementation patterns.
jeremylongshore
Skill Author
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