Hyperparameter tuning is a critical phase in the machine learning workflow, directly impacting the performance and generalization ability of models. Understanding when to calibrate hyperparameters requires a solid grasp of both the machine learning process and the function of hyperparameters within it. Hyperparameters are configuration variables that are set prior to the commencement of the