E-commerce websites like Amazon make use of Machine Learning to recommend products to their customers. The basic idea of this kind of recommendation comes from collaborative filtering. Collaborative filtering is the process of comparing users with similar shopping behaviors in order to recommend products to a new user with similar shopping behavior.
The “People who bought this also bought…” recommendations seen on Amazon are typically based on collaborative filtering algorithms. Collaborative filtering is a method used in recommendation systems that makes predictions (filtering) about the interests of a user by collecting preferences or taste information from many users (collaborating). It works by searching for patterns of ratings or preferences among multiple users to make recommendations. This could include techniques such as user-based collaborative filtering or item-based collaborative filtering.