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Machine Learning for Streaming Data with Python

You're reading from   Machine Learning for Streaming Data with Python Rapidly build practical online machine learning solutions using River and other top key frameworks

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Product type Paperback
Published in Jul 2022
Publisher Packt
ISBN-13 9781803248363
Length 258 pages
Edition 1st Edition
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Author (1):
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Joos Korstanje Joos Korstanje
Author Profile Icon Joos Korstanje
Joos Korstanje
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Toc

Table of Contents (17) Chapters Close

Preface 1. Part 1: Introduction and Core Concepts of Streaming Data
2. Chapter 1: An Introduction to Streaming Data FREE CHAPTER 3. Chapter 2: Architectures for Streaming and Real-Time Machine Learning 4. Chapter 3: Data Analysis on Streaming Data 5. Part 2: Exploring Use Cases for Data Streaming
6. Chapter 4: Online Learning with River 7. Chapter 5: Online Anomaly Detection 8. Chapter 6: Online Classification 9. Chapter 7: Online Regression 10. Chapter 8: Reinforcement Learning 11. Part 3: Advanced Concepts and Best Practices around Streaming Data
12. Chapter 9: Drift and Drift Detection 13. Chapter 10: Feature Transformation and Scaling 14. Chapter 11: Catastrophic Forgetting 15. Chapter 12: Conclusion and Best Practices 16. Other Books You May Enjoy

Summary

In this final chapter, you have seen a list of best practices that will help you to be successful and efficient while implementing this theory in practice. Finally, you have seen two potential learning paths that you may want to follow when continuing your learning journey into streaming analytics and online models.

With this, we have come to the end of this book. I hope that the book has been useful to you and that you will be successful in applying the topics in practice. It was a pleasure writing about this topic, which I am sure is going to gain a lot of traction soon. It will be one of the topics to look out for in the next trends of data science and machine learning. Of course, feel free to follow the publisher and me online for many new materials on streaming, data science, and more related topics to be published soon.

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