Question: Explain the term 'hyperparameter tuning' in the context of machine learning.

Answer: Hyperparameter tuning involves optimizing the hyperparameters of a machine learning model to achieve better performance. Techniques include grid search, random search, and more advanced methods like Bayesian optimization.

Example:

Adjusting the learning rate and the number of hidden layers in a neural network to maximize accuracy.