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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

Resources for learning about network analysis

So, what is needed to begin a journey into network thinking? I’ll give a few suggestions just to help you get started, but be aware that by the time this book has been published, some of this might already be a bit outdated and new technologies and techniques may have emerged. This is not a complete list. It is the bare minimum. The first thing that you need is a curious mind. If you are willing to investigate the hidden networks that make up our existence, then you already have the first prerequisite. Still, let me give you some more suggestions.

Notebook interfaces

I do all of my network analysis in Jupyter Notebooks. You can download and install Jupyter via Anaconda at: https://docs.anaconda.com/anaconda/install.

If you don’t want to install Jupyter, you can also use Google Colab without any installation. You can find and immediately start using Google Colab at https://research.google.com/colaboratory.

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