Key Features
Gain a deep understanding of how hyperparameter tuning works
Explore exhaustive search, heuristic search, and Bayesian and multi-fidelity optimization methods
Learn which method should be used to solve a specific situation or problem
Book Description
Hyperparameters are an important element in building useful machine learning models. This book curates numerous hyperparameter tuning methods for Python, one of the most popular coding languages for machine learning. Alongside in-depth explanations of how each method works, you will use a decision map that can help you identify the best tuning method for your requirements. .eText ISBN: 9781803241944
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