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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
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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

In this chapter, we covered what NLP is, how it has helped me, some common and advanced uses of NLP, and how a beginner can get started.

I hope this chapter gave you a rough idea of what NLP is, what it can be used for, what text analysis looks like, and some resources for more learning. This chapter is in no way the complete picture of NLP. It was difficult to even write the history, as there is just so much to the story and so much that has been forgotten over time.

Thank you for reading. This is my first time writing a book, and this is my first chapter ever written for a book, so this really means a lot to me! I hope you are enjoying this so far, and I hope I gave you an adequate first look into NLP.

Next up: network science and social network analysis!

You have been reading a chapter from
Network Science with Python
Published in: Feb 2023
Publisher: Packt
ISBN-13: 9781801073691
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