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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

Product type Paperback

Published in Apr 2023

Publisher Packt

ISBN-13 9781803246451

Length 394 pages

Edition 1st Edition

Languages

Python

Tools

BERT

Concepts

Data Science

Author (1):

Duc Haba

View More author details

Table of Contents (17) Chapters

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

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16. Other Books You May Enjoy

Index

As this ebook edition doesn't have fixed pagination, the page numbers below are hyperlinked for reference only, based on the printed edition of this book.

A

access token 31

additive Chi2 kernel 358

Albumentations 81

reference link 81

Amazon reviews dataset 53-57

American Multi-Cinema (AMC) 7

American National Standards Institute (ANSI) 153

amplitude 236

Antares Auto-Tune Pro 237

ARIMA 348

artificial neural network (ANN) algorithm 4

ASCII value 237

audio augmentation 235

libraries 243

audio control clip 248

audio definition 7

audio filters 240

Audiomentations 243, 244

reference link 243

audio Spectrogram 294-297

audio Waveform graph

listening 249-252

viewing 249-252

Augly 81, 155, 243

reference link 81

autoencoders 358

autoregressive integrated moving average (ARIMA) 317

Autotune 237

B

background noise 240

background noise injection method 273

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Authors (1)

Duc Haba

Duc Haba

Mr. Duc Haba is a lifelong technologist and researcher specializing in Deep Learning and Generative AI. He has been a programmer, Enterprise Mobility Solution Architect, AI Solution Architect, Principal, VP, CTO, and CEO. The companies range from startups and IPOs to enterprise companies. Duc's career started with Xerox Palo Alto Research Center (PARC), researching expert systems (ruled-based) for Xerox copier diagnostics. After PARC, he joined Oracle, following Viant Consulting as a founding member. He jumped headfirst into the entrepreneurial culture in Silicon Valley. There were slightly more failures than successes, but the highlights are working with Oracle, Viant, and RRKidz. Currently, he is happy working at YML as the AI Solution Architect.

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