What is a hyperparameter in machine learning?

A hyperparameter is a parameter that is set before training a machine learning model and cannot be learned from the data. Hyperparameters control the behavior and performance of the model, such as the learning rate, regularization strength, or the number of hidden layers in a neural network. Hyperparameters are usually set by trial and error, or by using automated techniques such as grid search or Bayesian optimization.