Question: When a machine learning model performs very well on the training data but poorly on the testing data, what challenge is this model experiencing? When

When a machine learning model performs very well on the training data but poorly on the testing data, what challenge is this model experiencing? When a machine learning model performs very well on the training data but poorly on the testing data, what challenge is this model experiencing? Non-representative data Poor-quality data Overfitting Underfitting

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