gccrpm/Recommender-System-for-Movies-using-Boltzmann-Machine

From Amazon product suggestions to Netflix movie recommendations - good recommender systems are very valuable in today's World. And specialists who can create them are some of the top-paid Data Scientists on the planet. I work on a dataset that has exactly the same features as the Netflix dataset: plenty of movies, thousands of users, who have rated the movies they watched. The ratings go from 1 to 5, exactly like in the Netflix dataset, which makes the Recommender System more complex to build than if the ratings were simply “Liked” or “Not Liked”. Final Recommender System will be able to predict the ratings of the movies the customers didn’t watch. Accordingly, by ranking the predictions from 5 down to 1, your Deep Learning model will be able to recommend which movies each user should watch. Creating such a powerful Recommender. Our f model Deep Belief Networks, complex Boltzmann Machines that will be covered for recommender system. The list of movies will be explicit so simply need to rate the movies you already watched, input your ratings in the dataset, execute model and voila! The Recommender System tell you exactly which movies you would love one night you if are out of ideas of what to watch on Netflix!

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