Traditionally, hyperparameters were tuned manually by trial and error. This is still commonly done, and experienced operators can “guess” parameter values that will achieve remarkably high accuracy for deep learning models. However, there is a constant search for better, faster, and more automatic methods to optimize hyperparameters.