Movie Recommendation System Machine Learning Project at Movie

Movie Recommendation System Machine Learning Project. This data consists of 105339 ratings applied over 10329 movies. They are used to predict the rating or preference that a user would give to an item.

Every time you shop online, a recommendation system is guiding you towards the most likely product you might purchase. Building movie recommender machine learning model to build our model, we first create a count matrix that is created by the help of a count vectorizer. Recommender systems are utilized in a variety of areas including movies, music, news, books, research articles, search queries, social tags, and products in general.

Explore and run machine learning code with kaggle notebooks | using data from the movies dataset Movie recommendation system python project report. Recommender systems are machine learning systems that help users discover new products and services. Our project entitled “movie recommendation system” aims to suggest or recommend the various users, the movie they might like, by intake of their ratings, comments and history.