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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

Chapter 6: Online Classification

In the previous two chapters, you were introduced to some basic notions of classification. You first saw a use case in which online classification models in River were used to build a model that can identify an iris species based on a number of characteristics of a plant. This iris dataset is one of the best-known datasets in the world and is a very common starting point for classification.

After that, you looked at anomaly detection. We discussed how classification models can be used for anomaly detection for those cases where we can label anomalies as one class and non-anomalies as another class. Specific anomaly detection models are often better at the task, as they strive to understand only the non-anomalies. Classification models will strive to understand each of the classes.

In this chapter, you'll go much deeper into classification. The chapter will start by posing definitions of what classification is and what it can be used for....

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