Movie recommendations are used to predict movies for users based on their interests. The content in the database is filtered and an appropriate movie is recommended for the user. Having the appropriate movie recommended increases the probability of the user purchasing the movie. Collaborative filtering is used to build the movie recommendation system. It considers the behavior of the current user in the past. It also considers the ratings given by my other users. Collaborative filtering involves finding and computing the Euclidean distance, Pearson correlation, and finding similar users in the dataset.
Introduction
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