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