Movie-Recommendation-System-using-collaborative-filtering-machine-learning-and-deep-learning

The rise of streaming platforms has led recommendation system to evolve at a rapid pace as well. However, certain algorithms perform better at doing the recommendation which will be studied and compared in detail in accordance with movie recommendation. We divided the models according to recommendation system using implicit feedback and explicit feedback. Both incorporated collaborative filtering in their system where we focused on finding similar users to predict the movies which the user might like and highly rate. Under the explicit feedback system, we compared the weighted average rating method using cosine similarity with machine learning models such as KNN, SVD and SlopeOne classifiers. For the implicit feedback system, we used deep learning models which incorporated neural collaborative filtering to predict movies for a user based on his past viewed history. To find out the accuracy of the explicit feedback system we used RMSD and Recall whereas hitrate@10 was better suited to evaluate the implicit deep learning model.