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Recommendation Engine 0.1 ============================= My goal is to build a simple recommendation engine where anyone can play with their datasets. Though I have tested it on Movielens dataset of 1 million ratings, I don't think the current version will be able to process any realistic size dataset. The reason I think is that all the data that is the ratings and user and movie information is stored in the memory. If you find any issues, Please do email me at firstname.lastname@example.org Input Format ============================ The input format for the recommendation engine is of the form:- user_id,item_id,rating,timestamp the separator can be anything and the timestamp attribute is optional. It is assumed that the user range from 1 to n and the items range from 1 to m For more information on usage please refer to Example.py for a sample usage.