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🍿 A movie recommender system built with hadoop and spark using the ALS collaborative filtering algorithm.

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Movie Reccomender System with ALS collaborative filtering

In the current world, movies serve as a remarkably interesting topic of study as it is a major part of the lives of the majority of people in the world. Performing analysis on the dataset for movies can be used to grab a lot of insights on the movie trends and how the industry can improve their marketing strategies based on time of release, genre, location etc.

This project also aims at building a movie recommender system to help the audience navigate through the movie universe in an easy way and with minimum hassle. The system is built using the ALS (Alternating Least Squares) algorithm under collaborative filtering. Hence, doing an explorative study on this subject proved to an overly exciting opportunity.

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🍿 A movie recommender system built with hadoop and spark using the ALS collaborative filtering algorithm.

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  • Python 100.0%