You're reading from Synthetic Data for Machine Learning Revolutionize your approach to machine learning with this comprehensive conceptual guide

Product type Paperback

Published in Oct 2023

Publisher Packt

ISBN-13 9781803245409

Length 208 pages

Edition 1st Edition

Concepts

Data Science

Author (1):

Abdulrahman Kerim

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Table of Contents (25) Chapters

Preface

1. Part 1:Real Data Issues, Limitations, and Challenges

2. Chapter 1: Machine Learning and the Need for Data FREE CHAPTER

3. Chapter 2: Annotating Real Data

4. Chapter 3: Privacy Issues in Real Data

5. Part 2:An Overview of Synthetic Data for Machine Learning

6. Chapter 4: An Introduction to Synthetic Data

7. Chapter 5: Synthetic Data as a Solution

8. Part 3:Synthetic Data Generation Approaches

9. Chapter 6: Leveraging Simulators and Rendering Engines to Generate Synthetic Data

10. Chapter 7: Exploring Generative Adversarial Networks

11. Chapter 8: Video Games as a Source of Synthetic Data

12. Chapter 9: Exploring Diffusion Models for Synthetic Data

13. Part 4:Case Studies and Best Practices

14. Chapter 10: Case Study 1 – Computer Vision

15. Chapter 11: Case Study 2 – Natural Language Processing

16. Chapter 12: Case Study 3 – Predictive Analytics

17. Chapter 13: Best Practices for Applying Synthetic Data

18. Part 5:Current Challenges and Future Perspectives

19. Chapter 14: Synthetic-to-Real Domain Adaptation

20. Chapter 15: Diversity Issues in Synthetic Data

21. Chapter 16: Photorealism in Computer Vision

22. Chapter 17: Conclusion

23. Index

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Table of Contents (25) Chapters

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