July 2022
Intermediate to advanced
306 pages
7h 36m
English
Overview
"Hyperparameter Tuning with Python" is your go-to resource for mastering the art of fine-tuning machine learning models. This book provides detailed guidance on various hyperparameter optimization techniques and tools, tailored specifically for Python practitioners. By following this book, you will learn how to systematically enhance your model performance using advanced methods.
What this Book will help me do
- Understand the principles of hyperparameter optimization, including the roles of hyperparameters and their distributions.
- Discover and employ a variety of optimization techniques such as grid search, random search, Bayesian optimization, and heuristic approaches.
- Master popular Python frameworks for hyperparameter tuning, including Scikit-learn, Hyperopt, and Optuna.
- Develop the skills to analyze and tune the hyperparameters of major machine learning algorithms effectively.
- Learn to implement hyperparameter tuning in real-world scenarios using best practices and decision maps.
Author(s)
Louis Owen is an experienced machine learning practitioner with years of hands-on expertise in building and optimizing machine learning models. With a strong background in Python-based data science, Louis has helped organizations achieve significant improvements in their AI solutions. His approach in writing focuses on delivering practical knowledge coupled with deep technical insights to empower learners.
Who is it for?
This book is tailored for data scientists and machine learning engineers who have experience in Python and wish to elevate their skills in model optimization. If you're looking to enhance the performance of your machine learning models by choosing the optimal hyperparameter tuning methods, this book is for you. Readers should have a grasp of Python programming and basic machine learning concepts but need no prior experience with hyperparameter tuning. Whether you're refining existing skills or exploring new techniques, this book will serve as an invaluable resource.
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