Hyperparameter Tuning

The process of optimising the configuration parameters that control the learning process of a machine learning model, which are set before training begins.

Adjusting the settings that control how an AI learns; like choosing the learning speed, model size or number of training rounds. It's like adjusting the temperature and time when baking to get the best results.