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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24. Other Books You May Enjoy

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You will need a version of PyCharm installed on your computer – the latest version, if possible. All code examples have been tested using Python 3.8 and PyCharm 2023.1 (Professional Edition) on Ubuntu 20.04.2 LTS. However, they should work with future version releases, too.

Software/hardware covered in the book	Operating system requirements
Python 3.8+	Windows, macOS, or Linux
PyCharm 2023.1	Windows, macOS, or Linux

If you are using the digital version of this book, we advise you to type the code yourself or access the code from the book’s GitHub repository (a link is available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.

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Table of Contents (25) Chapters

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