a learning curve shows the validation and training score of an estimator for varying numbers of training samples. it is a tool to find out how much a machine learning model benefits from adding more training data and whether the estimator suffers more from a variance error or a bias error. if both the validation score and the training score converge to a value that is too low with increasing size of the training set, it will not benefit much from more training data.