Different types of Matrix Factorization Techniques and Scaling mechanisms for online Recommendation Engines Introduction Low-rank approximations of data matrices have become an important tool in Machine Learning in the field of bio-informatics, computer vision, text processing, recommender systems, and others. They provide efficient compact representation of multi-dimensional vectors by embedding high dimensional data in lower dimensional spaces. In such representations, it comes to rescue by mitigating noise, unfolding latent relations, and facilitates further processing. In […]
