At the training step, there are two important parameters to mention: epochs, defined as each complete training iteration, and batch size, which is the number of training samples used at each update of model parameters. The definition of these parameters is crucial because too few epochs could result in a model with a low accuracy, while too many require a substantial computational effort with an increased risk of overfitting.