Implement collaborative filtering algorithm for recommendations

Overview

Implement a user-based collaborative filtering algorithm to generate personalized recommendations.

Requirements

• Matrix factorization using SVD
• User-item interaction matrix
• Similarity computation (cosine similarity)
• Top-N recommendation generation

Tech Stack

• Python 3.11+
• NumPy, SciPy
• scikit-learn
• Redis for caching

Acceptance Criteria

• Algorithm achieves 85%+ precision@10
• Response time < 50ms for cached results
• Unit tests with >90% coverage