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Data Labeling in Machine Learning with Python

You're reading from   Data Labeling in Machine Learning with Python Explore modern ways to prepare labeled data for training and fine-tuning ML and generative AI models

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Product type Paperback
Published in Jan 2024
Publisher Packt
ISBN-13 9781804610541
Length 398 pages
Edition 1st Edition
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Author (1):
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Vijaya Kumar Suda Vijaya Kumar Suda
Author Profile Icon Vijaya Kumar Suda
Vijaya Kumar Suda
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Table of Contents (18) Chapters Close

Preface 1. Part 1: Labeling Tabular Data
2. Chapter 1: Exploring Data for Machine Learning FREE CHAPTER 3. Chapter 2: Labeling Data for Classification 4. Chapter 3: Labeling Data for Regression 5. Part 2: Labeling Image Data
6. Chapter 4: Exploring Image Data 7. Chapter 5: Labeling Image Data Using Rules 8. Chapter 6: Labeling Image Data Using Data Augmentation 9. Part 3: Labeling Text, Audio, and Video Data
10. Chapter 7: Labeling Text Data 11. Chapter 8: Exploring Video Data 12. Chapter 9: Labeling Video Data 13. Chapter 10: Exploring Audio Data 14. Chapter 11: Labeling Audio Data 15. Chapter 12: Hands-On Exploring Data Labeling Tools 16. Index 17. Other Books You May Enjoy

Real-world examples for video data labeling

Here are some real-world companies from various industries along with their use cases for video data analysis and labeling:

  • A retail company – a Walmart use case: Walmart utilizes video data analysis for customer behavior tracking and optimizing store layouts. By analyzing video data, it gains insights into customer traffic patterns, product placement, and overall store performance.
  • A finance company – a JPMorgan Chase & Co. use case: JPMorgan Chase & Co. employs video data analysis for fraud detection and prevention. By analyzing video footage from ATMs and bank branches, it can identify suspicious activities, detect fraud attempts, and enhance security measures.
  • An e-commerce company – an Amazon use case: Amazon utilizes video data analysis for package sorting and delivery optimization in its warehouses. By analyzing video feeds, it can track packages, identify bottlenecks in the sorting process...
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