Content Based Movie Recommendation System

A recommendation system is a system that suggests resources to the user like books, movies, song, etc. based on some dataset. A movie recommender system usually generates opinion about what the user would like to view, but it is always a cumbersome task to select a movie because the dataset of movies around the world is large. Although, this issue can be resolved with the help of a movie Recommendation System (RS), which uses content-based filtering. This RS recommends movies to the users based on the content they are searching and watching. In this article, a dataset from Kaggle is used for the implementation of content-based filtering using machine learning (cosine similarities) with vectorization and the data analysis tool used is Python.