Introduction to Hyperparameter Optimization
Explore the fundamentals of hyperparameter optimization and understand its importance in improving machine learning models. This lesson covers why tuning hyperparameters boosts performance, helps prevent overfitting, and saves time by automating searches for optimal settings. You'll gain the foundational knowledge needed to start optimizing models effectively.
What is hyperparameter optimization?
Hyperparameter optimization, also known as hyperparameter tuning, is the process of finding the best combination of hyperparameters for a given model and dataset to achieve maximum performance in a reasonable amount of time. This can be done through a manual process of trial and error. However, it is often more efficient to use automated techniques such as grid search, random search, or Bayesian optimization.
Most of these ML algorithms come with the default hyperparameter values, and they often don’t produce ML models with the best performance. Therefore, optimizing their values can help to identify the best combination that ...