Web Reference: Sep 5, 2025 · Hyperparameter tuning is the process of selecting the best parameters to maximize the efficiency and accuracy of the model. We'll explore three common techniques: GridSearchCV, RandomizedSearchCV and Optuna. We will use Titanic dataset for demonstration. 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. This book is for data scientists and ML engineers who are working with Python and want to further boost their ML model’s performance by using the appropriate hyperparameter tuning method.
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