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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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Toc

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

Applying image augmentation with Albumentations

More often than not, in machine learning (ML), data is crucial to getting better performances of models. Computer vision is no exception, and data augmentation with images can be easily taken to another level.

Indeed, it is possible to easily augment an image, for example, by mirroring it, as shown in Figure 11.1.

Figure 11.1 – On the left, the original picture of my dog, and on the right, a mirrored picture of my dog

Figure 11.1 – On the left, the original picture of my dog, and on the right, a mirrored picture of my dog

However, beyond this, many more types of augmentation are possible and can be divided into two main categories: pixel-level and spatial-level transformations.

Let's discuss both of these in the following sections.

Spatial-level augmentation

The mirroring is an example of spatial-level augmentation; however, much more than simple mirroring can be done. For example, see the following:

  • Shifting: Shifting an image in a certain direction
  • Shearing: Add shearing...
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