A movie recommendation system is a type of recommendation system that suggests movies to users based on their preferences and viewing history. It uses machine learning algorithms to analyze various factors such as genre, cast and ratings to provide personalized movie recommendations to users. This movie recommendation system uses content based filtering by cosine similarity to recommend the movies based on parameters and on users past history. The movie recommendation system provides a seamless and personalized movie watching experience, tailored to the individual preferences of each user, ultimately increasing user satisfaction.
Our recommendation system allows users to search movies and give ratings according to their experience and we provide the recommendation according to that movie so that users can watch similar types of content. Recommendations are also provided by including all the movies liked by the user so far which will be stored in our database. Recommendations according to the user's favourite genre or cast are also provided. According to the ratings collected from all the users we can analyse the movies. Top movies can then be shown to other users.