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Content Based MOVIE RECOMMENDER SYSTEM
Content Based MOVIE RECOMMENDER SYSTEM
Our unsupervised, machine learning solution takes 'The Movies Dataset' as input and uses movies' features like genre, keywords and actors to recommend movies that a similar to a given movie. Cosine Similarity is used to find the movies similar to each other.
Our unsupervised, machine learning solution takes 'The Movies Dataset' as input and uses movies' features like genre, keywords and actors to recommend movies that a similar to a given movie. Cosine Similarity is used to find the movies similar to each other.
collaborative filtering RecommendER System
collaborative filtering RecommendER System
Our solution uses the information about the movies watched and ratings given by the users to find similar users. Similar users are the ones which give same ratings to similar movies. The objective of collaborative filtering system is to recommend those movies to a user that are liked by users similar to him/her. This is an unsupervised, deep learning solution which is an implementation of autoencoders in Tensorflow.
Our solution uses the information about the movies watched and ratings given by the users to find similar users. Similar users are the ones which give same ratings to similar movies. The objective of collaborative filtering system is to recommend those movies to a user that are liked by users similar to him/her. This is an unsupervised, deep learning solution which is an implementation of autoencoders in Tensorflow.
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