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

Part 4:Case Studies and Best Practices

In this part, you will be introduced to rich and diverse case studies in three cutting-edge areas in the field of ML: Computer Vision (CV), Natural Language Processing (NLP), and Predictive Analytics (PA). You will comprehend the benefits of employing synthetic data in these fields and identify the main challenges and issues. Following this, you will learn about best practices that improve the usability of synthetic data in practice.

This part has the following chapters:

Chapter 10, Case Study 1 – Computer Vision
Chapter 11, Case Study 2 – Natural Language Processing
Chapter 12, Case Study 3 – Predictive Analytics
Chapter 13, Best Practices for Applying Synthetic Data

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

Table of Contents (25) Chapters

Part 4:Case Studies and Best Practices

Authors (1)

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

Table of Contents (25) Chapters

Part 4:Case Studies and Best Practices

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