What is overfitting in machine learning?

Answer

Overfitting happens when a model learns the training data too closely, including its noise and quirks, so it performs well on that data but poorly on new, unseen inputs. It usually signals that the model is too complex relative to the amount of data or that training ran too long. Common remedies include more or more varied training data, regularization, dropout, cross-validation, and early stopping.