A recommendation engine is a model that can predict what a user may be interested in. When we apply this to the context of movies, for example, this becomes a movie recommendation engine. We filter items in our database by predicting how the current user might rate them. This helps us in connecting the user to the right content in our dataset. Why is this relevant? If you have a massive catalog, then the user may or may not find all the content that is relevant to them. By recommending the right content, you increase consumption. Companies such as Netflix heavily rely on recommendations to keep the user engaged.
Recommendation engines usually produce a set of recommendations using either collaborative filtering or content-based filtering. The difference between the two approaches is in the way that the recommendations are mined. Collaborative...
