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Data Augmentation with Python

You're reading from  Data Augmentation with Python

Product type Book
Published in Apr 2023
Publisher Packt
ISBN-13 9781803246451
Pages 394 pages
Edition 1st Edition
Languages
Author (1):
Duc Haba Duc Haba
Profile icon Duc Haba
Toc

Table of Contents (17) Chapters close

Preface 1. Part 1: Data Augmentation
2. Chapter 1: Data Augmentation Made Easy 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

Initializing and downloading

Start with loading the data_augmentation_with_python_chapter_8.ipynb file on Google Colab or your chosen Python Notebook or JupyterLab environment. From this point onward, the code snippets are from the Python Notebook, which contains the complete functions.

The following initializing and downloading steps should be familiar to you because we have done them six times. The following code snippet is the same as from Chapter 7:

# Clone GitHub repo.
url = 'https://github.com/PacktPublishing/Data-Augmentation-with-Python'
!git clone {url}
# Intialize Pluto from Chapter 7
pluto_file = 'Data-Augmentation-with-Python/pluto/pluto_chapter_7.py'
%run {pluto_file}
# Verify Pluto
pluto.say_sys_info()
# Fetch Musical emotions classification
url = 'https://www.kaggle.com/datasets/kingofarmy/musical-emotions-classification'
pluto.fetch_kaggle_dataset(url)
f = 'kaggle/musical-emotions-classification/Train.csv'
pluto.df_music_data...
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