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Network Science with Python

You're reading from   Network Science with Python Explore the networks around us using network science, social network analysis, and machine learning

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Product type Paperback
Published in Feb 2023
Publisher Packt
ISBN-13 9781801073691
Length 414 pages
Edition 1st Edition
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Author (1):
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David Knickerbocker David Knickerbocker
Author Profile Icon David Knickerbocker
David Knickerbocker
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Table of Contents (17) Chapters Close

Preface 1. Part 1: Getting Started with Natural Language Processing and Networks
2. Chapter 1: Introducing Natural Language Processing FREE CHAPTER 3. Chapter 2: Network Analysis 4. Chapter 3: Useful Python Libraries 5. Part 2: Graph Construction and Cleanup
6. Chapter 4: NLP and Network Synergy 7. Chapter 5: Even Easier Scraping! 8. Chapter 6: Graph Construction and Cleaning 9. Part 3: Network Science and Social Network Analysis
10. Chapter 7: Whole Network Analysis 11. Chapter 8: Egocentric Network Analysis 12. Chapter 9: Community Detection 13. Chapter 10: Supervised Machine Learning on Network Data 14. Chapter 11: Unsupervised Machine Learning on Network Data 15. Index 16. Other Books You May Enjoy

Summary

We did it! We made it to the end of another chapter. I truly hope you found this chapter especially interesting because there are so few sources that explain how to do this from scratch. One of the reasons I decided to write this book is because I was hoping that ideas like this would take off. So, I hope this chapter grabbed your attention and sparked your creativity.

In this chapter, we transformed an actual network into training data that we could use for machine learning. This was a simplified example, but the steps will work for any network. In the end, we created a model that was able to identify members of Friends of the ABC revolutionary group, though it was a very simple model and not suitable for anything real-world.

The next chapter is going to be very similar to this one, but we will be using unsupervised ML to identify nodes that are similar to other nodes. Very likely, unsupervised ML will also identify members of Friends of the ABC, but it will likely also...

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