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The Regularization Cookbook

You're reading from   The Regularization Cookbook Explore practical recipes to improve the functionality of your ML models

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Product type Paperback
Published in Jul 2023
Publisher Packt
ISBN-13 9781837634088
Length 424 pages
Edition 1st Edition
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Author (1):
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Vincent Vandenbussche Vincent Vandenbussche
Author Profile Icon Vincent Vandenbussche
Vincent Vandenbussche
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Table of Contents (14) Chapters Close

Preface 1. Chapter 1: An Overview of Regularization 2. Chapter 2: Machine Learning Refresher FREE CHAPTER 3. Chapter 3: Regularization with Linear Models 4. Chapter 4: Regularization with Tree-Based Models 5. Chapter 5: Regularization with Data 6. Chapter 6: Deep Learning Reminders 7. Chapter 7: Deep Learning Regularization 8. Chapter 8: Regularization with Recurrent Neural Networks 9. Chapter 9: Advanced Regularization in Natural Language Processing 10. Chapter 10: Regularization in Computer Vision 11. Chapter 11: Regularization in Computer Vision – Synthetic Image Generation 12. Index 13. Other Books You May Enjoy

An Overview of Regularization

Let’s embark on a journey into the world of regularization in machine learning. I hope you will learn a lot and find as much joy in reading this book as I did in writing it.

Regularization is important for any individual willing to deploy robust machine learning (ML) models.

This chapter will introduce some context and key concepts about regularization before diving deeper into it in the next chapters. At this point, you may have many questions about this book and about regularization in general. What is regularization? Why do we need regularization for production-grade ML models? How do we diagnose the need for regularization? What are the limits of regularization? What are the approaches to regularization?

All the foundational knowledge about regularization will be provided in this chapter in the hope of answering all these questions. Not only will this give you a high-level understanding of what regularization is but it will also allow...

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