9 Machine Learning Algorithms For Recommendation Engines
Building Recommender Systems with Machine Learning and AI Such an approach effectively addresses the issue of working with sparse data and reflects more subtle user and movie relations and provides recommendations. Matrix factorization is a technique often used in collaborative filtering to reduce the user-item interaction matrix into lower-dimensional matrices. This allows the system to discover hidden relationships between users and items by capturing latent factors. Popular techniques include Singular… Read More »9 Machine Learning Algorithms For Recommendation Engines
