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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

There are other Python libraries that we will use in this book, but they will be explained in their relevant chapters. In this chapter, I wanted to describe the primary libraries we will use for our work. In order to get to the really experimental stuff that we cover in this book, a foundation needs to be in place.

For instance, you need to be able to read and analyze tabular (structured) data. You also need to be able to visualize data. With text, you need to be able to convert text into a format that is ready for analysis and use. For graphs, you need to be able to do the same. And finally, if you want to apply machine learning to networks or text, you should understand how to do that.

That is why the sections have been broken down into data analysis and processing, data visualization, natural language processing, network analysis and visualization, and machine learning. I hope the structure helps.

With these libraries installed and briefly explained, we are now...

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