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Data Augmentation with Python

You're reading from   Data Augmentation with Python Enhance deep learning accuracy with data augmentation methods for image, text, audio, and tabular data

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Product type Paperback
Published in Apr 2023
Publisher Packt
ISBN-13 9781803246451
Length 394 pages
Edition 1st Edition
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Author (1):
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Duc Haba Duc Haba
Author Profile Icon Duc Haba
Duc Haba
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Toc

Table of Contents (17) Chapters Close

Preface 1. Part 1: Data Augmentation
2. Chapter 1: Data Augmentation Made Easy FREE CHAPTER 3. Chapter 2: Biases in Data Augmentation 4. Part 2: Image Augmentation
5. Chapter 3: Image Augmentation for Classification 6. Chapter 4: Image Augmentation for Segmentation 7. Part 3: Text Augmentation
8. Chapter 5: Text Augmentation 9. Chapter 6: Text Augmentation with Machine Learning 10. Part 4: Audio Data Augmentation
11. Chapter 7: Audio Data Augmentation 12. Chapter 8: Audio Data Augmentation with Spectrogram 13. Part 5: Tabular Data Augmentation
14. Chapter 9: Tabular Data Augmentation 15. Index 16. Other Books You May Enjoy

Reinforcing learning through Python Notebook

Pluto uses the Python Notebook to reinforce our understanding of text augmentation. He uses the batch function to display text in batches. This works similarly to the batch functions for images. In other words, it randomly selects new records and transforms them using the augmentation methods.

Fun fact

Pluto recommends running the batch functions repeatedly to gain a deeper insight into the text augmentation methods. There are thousands of text records in the Twitter and Amazon datasets. Each time you run the batch functions, it displays different records from the dataset.

As with the image augmentation implementation, the wrapper functions use the Nlpaug library under the hood. The wrapper function allows you to focus on the text transformation concepts and not be distracted by the library implementation. You can use another text augmentation library, and the wrapper function input and output will remain the same.

Pluto could...

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