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User-based Movie Recommender system

User-based Collaborative Filtering Movie Recommender based on MovieLens dataset

# Steps

  • Identify and prepare the data
  • Find Similar users based on interactions with common items
  • Identify items rated highly by similar users but the target user has not been exposed to or interacted with
  • Calculate the weighted average score for each item
  • Rank items based on score and recommend top “n” items