Machine learning uses algorithms to turn a data set into a model that can identify patterns or make predictions from new data. Which algorithm works best depends on the problem.

The choice of the optimal hyperparameters is more art than science, if we want to run it manually. Indeed, the optimal selection of the hyperparameter values depends on the problem at hand.