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Fairness in Machine Learning with PyTorch
Elitist shuffle for recommendation systems
In today's high pace user experience it is expected that new recommended items appear every time the user opens the application, but what to do if your recommendation system runs every hour or every day? I give a solution that you can plug & play without having to re-engineer your recommendation system.