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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

Product type Paperback

Published in Jul 2023

Publisher Packt

ISBN-13 9781837634088

Length 424 pages

Edition 1st Edition

Languages

Ring

Tools

Astro

Concepts

Machine Learning

Author (1):

Vincent Vandenbussche

View More author details

Table of Contents (14) Chapters

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

Why subscribe?

13. Other Books You May Enjoy

Technical requirements

In this section, we will train CNNs, object detection, and semantic segmentation models, requiring the following libraries:

NumPy
scikit-learn
Matplotlib
PyTorch
torchvision
Ultralytics
segmentation-models-pytorch

The rest of the chapter is locked

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Authors (1)

Vincent Vandenbussche

Vincent Vandenbussche

Since gaining a Ph.D. in physics, Vincent Vandenbussche has worked for a decade in diverse companies, deploying ML solutions at scale. He has worked at numerous companies, such as Renault, L'Oréal, General Electric, Jellysmack, Chanel, and CERN. He also has a passion for teaching; he co-founded a data science boot camp, was an ML lecturer at MINES ParisTech engineering school and EDHEC Business School, and trained numerous professionals at companies such as ArcelorMittal and Orange.

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