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/Introduction to Hyperparameter Optimization
Introduction to Hyperparameter Optimization
Understand the importance of hyperparameter optimization in developing high-performing ML models.
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 ...