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The project is used for dividing different groups of consumer from their past retail data. ML Algorithm named SAPK(Semi Supervised Affinity propagation) and K-Means is used for efficient segmentation of user group.
This project is a case study of the Movielens dataset, which contains anonymous ratings of approximately 3,900 movies made by 6,040 MovieLens users. The goal of the project is to explore the data, find features that affect movie ratings, and build a model to predict movie ratings.