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Hyperparameter Tuning with Python

You're reading from  Hyperparameter Tuning with Python

Product type Book
Published in Jul 2022
Publisher Packt
ISBN-13 9781803235875
Pages 306 pages
Edition 1st Edition
Languages
Author (1):
Louis Owen Louis Owen
Profile icon Louis Owen
Toc

Table of Contents (19) Chapters close

Preface 1. Section 1:The Methods
2. Chapter 1: Evaluating Machine Learning Models 3. Chapter 2: Introducing Hyperparameter Tuning 4. Chapter 3: Exploring Exhaustive Search 5. Chapter 4: Exploring Bayesian Optimization 6. Chapter 5: Exploring Heuristic Search 7. Chapter 6: Exploring Multi-Fidelity Optimization 8. Section 2:The Implementation
9. Chapter 7: Hyperparameter Tuning via Scikit 10. Chapter 8: Hyperparameter Tuning via Hyperopt 11. Chapter 9: Hyperparameter Tuning via Optuna 12. Chapter 10: Advanced Hyperparameter Tuning with DEAP and Microsoft NNI 13. Section 3:Putting Things into Practice
14. Chapter 11: Understanding the Hyperparameters of Popular Algorithms 15. Chapter 12: Introducing Hyperparameter Tuning Decision Map 16. Chapter 13: Tracking Hyperparameter Tuning Experiments 17. Chapter 14: Conclusions and Next Steps 18. Other Books You May Enjoy

Who this book is for

The book is intended for data scientists and Machine Learning engineers who are working with Python and want to further boost their ML model’s performance by utilizing the appropriate hyperparameter tuning method. You will need to have a basic understanding of ML and how to code in Python but will require no prior knowledge of hyperparameter tuning in Python.

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