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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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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 chapter, you were first introduced to the underlying foundations of reinforcement learning. You saw that reinforcement learning models are focused on taking actions rather than on making predictions.

You also saw two widely known algorithms for reinforcement learning. This started with Q-learning, which is the foundational algorithm of reinforcement learning, and its more powerful improvement, Deep Q-learning.

Reinforcement learning is often used for more advanced use cases such as chatbots or self-driving cars, but can also be used for numerical data streams very well. Through a use case, you saw how to apply reinforcement learning to streaming data for finance.

With this chapter, you have come to the end of discovering the most relevant machine learning models for online learning. In the coming chapters, you will discover a number of additional tools that you will need to take into account in online learning and that have no real counterpart in traditional...

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