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How to build a recommender system?
The document discusses building a recommender system using collaborative filtering approaches. It describes collecting usage and rating data, calculating item-item and user-user similarities, making predictions for unknown values using k-nearest neighbors, and evaluating the system using measures like precision, recall and root mean squared error. Implementation details like programming languages, databases and cloud infrastructure are also summarized.