Similar to Netflix, YouTube, and Hotstar, the movie recommendation platform will operate. The suggestions will be predicted using R packages while taking into account the customers’ tastes, star cast, genre, and browsing history. Still unsure about the benefits of this method. By informing the options approved by the variety of users, the system may be able to address all movie search shortcomings. In addition, the project may be developed using either one of two techniques: collaborative filtering or content-based filtering. When deciding what to watch or not, the collaborative will take into account a user’s prior movie-watching habits.
Contrarily, content-based filtering makes use of a number of distinct traits that are entirely determined by the summary and profile of a movie that was recently or previously seen. In all of these, it is possible to model the required movie suggestions exactly and amusingly using R tools like data.table, ggplot2, and recommenderlab. As a result, you must choose this platform as your project and thoroughly train it to categorise and propose movies with various themes and interests.