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Recommendation engines are a subclass of machine learning which generally deal with ranking or rating products / users. Loosely defined, a recommender system is a system which predicts ratings a user might give to a specific item. These predictions will then be ranked and returned back to the user.
Types of Recommendation system:
User based filtering - Building a model from user's past behavior as well as similar decisions made by other users. This model is used to predict items that user may have interest in.
Content based filtering - Utilizes a series of discrete characteristics of an item in order to recommend additional item with similar properties to the user.