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Microsoft Azure Machine Learning by Sumit Mund

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Building a recommendation system

Now, it would be worthwhile that you learn to build one by yourself. We will build a simple recommender system to recommend restaurants to a given user.

ML Studio includes three sample datasets, described as follows:

  • Restaurant customer data: This is a set of metadata about customers, including demographics and preferences, for example, latitude, longitude, interest, and personality.
  • Restaurant feature data: This is a set of metadata about restaurants and their features, such as food type, dining style, and location, for example, placeID, latitude, longitude, price.
  • Restaurant ratings: This contains the ratings given by users to restaurants on a scale of 0 to 2. It contains the columns: userID, placeID, and rating ...

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