Movie Recommendation System Based on Machine Learning using Profiling

With the increasing amount of data available, recommendation systems are important for helping users find relevant content. This paper introduces a movie recommendation system that uses user profiles and machine learning techniques to improve the user experience by offering personalized suggestions. We tested different machine learning methods, including k nearest neighbors (KNN), support vector machines (SVM), and neural networks. We used several datasets, such as MovieLens and Netflix Prize, to check how accurate the recommendations were and how satisfied users were with them.