recommender system algorithms

Recommender system algorithms analyze your past behavior, preferences, and similar users to predict what products, movies, or content you might like. They use methods like collaborative filtering, which finds patterns among many users, or content-based filtering, which focuses on item features you prefer. Sometimes, they combine both approaches in hybrid models. These algorithms help personalize your experience by suggesting relevant options, making it easier to discover new items aligned with your tastes without you searching extensively.