Structured Analysis on Movie Recommendation System using Machine Learning

Nowadays, the most common way to pass the time is to watch a movie. Using search engines, the user must wade through a sea of information to find the intended information. Helping consumers find content they like is where the Recommender System comes into play. Movies can be recommended in a variety of ways. Collaborative filtering is the best method. Recommendations based on previous viewing habits can help us find good movies. User interest models are used to anticipate the user's interests, and collaborative filtering uses these models to provide recommendations. Unknown information can be filtered out using machine learning methods. Combining content-based filtering and collaborative filtering is the goal of this essay, which uses the KNN algorithm to get the most relevant results. Because of this, the user would be able to view movies without having to spend additional time searching for the right one.