Helpful examples for configuring XGBoost model parameters (hyperparameters).
They are parameters in the programming sense (e.g. arguments to functions), but hyperparameters in the model sense (e.g. influence model behavior). Technically, model parameters are the trees and weights found by the learning algorithm.