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Found 3 Skills
Build recommendation systems with collaborative filtering, matrix factorization, hybrid approaches. Use for product recommendations, personalization, or encountering cold start, sparsity, quality evaluation issues.
Generate personalized content recommendations based on learner profiles, performance, preferences, and learning analytics. Use for adaptive learning systems, content discovery, and personalized guidance. Activates on "recommend content", "next best", "personalization", or "what should I learn next".
Intelligent recommendation system analysis tool that provides implementations of multiple recommendation algorithms, evaluation frameworks, and visual analysis. It requires user behavior data, product information, or rating data for use, supports recommendation algorithms such as collaborative filtering and matrix factorization, and generates personalized recommendation results and evaluation reports.