Movie Recommender based on the MovieLens Dataset (ml-100k) using item-item collaborative filtering.
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Updated
Oct 16, 2017 - Jupyter Notebook
Movie Recommender based on the MovieLens Dataset (ml-100k) using item-item collaborative filtering.
Recommend movies to users by RBMs, TruncatedSVD, Stochastic SVD and Variational Inference
User Based Movie Recommendation System based on Collaborative Filtering Using Netflix Movie Dataset
An android app that lets you search for movies and their cast, and helps you discover your taste of movies
Movie Recommendation Engine using PySpark
Machine learning powered model to recommend movies based on your interests written in python.
Orbital 2016
A movie app where user can browse movies using TMDB API and add them to their watch/liked list
This is a movie recommendation system that recommends movie based on the ratings given by the user, uses user-user collaborative filter, item-item collaborative filter and matrix factorisation
A recommendation and prediction engine to guide users to new movies
Collection of Recommendation Systems Examples
A recommender engine similar to those used by Netflix or Amazon.
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