Restaurant Ratings Experiment

November 20, 2018

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Building restaurant ratings recommender
Three separate datasets used as input to train the Azure Machine Learning Matchbox recommender consisting of the following files: • Restaurant features: This includes information about each restaurant, such as placeID, location, name, address, state, whether alcohol is served, smoking policy, dress code, accessibility, and price. • Restaurant customers: This includes a wide variety of personal attributes including the following: userID, smoker, drink level, dress preference, marital status, birth year, interests, personality traits, religion, favorite color, weight, height, and budget. • Restaurant ratings