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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
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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

Sentence augmenting

Augmenting at the sentence level is a powerful concept. It was not possible 5 years ago. You had to be working in an ML research company or a billionaire before accessing these acclaimed pre-trained models. Some transformer and large language models (LLMs) became available in 2019 and 2020 as open source, but they are generally for research. Convenient access to online AI servers via a GPU was not widely available at that time. The LLM and pre-trained models have recently become publicly accessible for incorporating them into your projects, such as the HuggingFace website. The salient point is that for independent researchers or students, LLM and pre-trained models only became accessible in mid-2021.

The sentence and word augmenting methods that use ML can’t be done dynamically as with methods using the Nlpaug library. In other words, you have to write and save the augmented text to your local or cloud disk space. The primary reason is that the augmentation...

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