You've trained a model that looks strong on the training set, but the gap to validation or real-world performance suggests it is memorizing patterns instead of generalizing. Your team wants to know how you would systematically diagnose and reduce the overfitting.
How would you approach solving a problem where your model overfits to the training data?
