Abstract: Pruning and/or quantizing a machine learning predictor or, in other words, a machine learning model such as a neural network is rendered more efficient if the pruning and/or quantizing is performed using relevance scores which are determined for portions of the machine learning predictor on the basis of an activation of the portions of the machine learning predictor manifesting itself in one or more inferences performed by the machine learning (ML) predictor.