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

Product type Paperback

Published in Feb 2023

Publisher Packt

ISBN-13 9781801073691

Length 414 pages

Edition 1st Edition

Languages

Python

Tools

PyTorch

Concepts

Machine Learning

Author (1):

David Knickerbocker

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Table of Contents (17) Chapters

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

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Part 2: Graph Construction and Cleanup

Network data does not always exist for research that is interesting to an analyst. The chapters in this part show how to pull text data from various online resources and convert text data into networks that can be analyzed. These chapters also walk through data wrangling steps for cleaning networks for use in analysis and downstream processes.

This section includes the following chapters:

Chapter 4, NLP and Network Synergy
Chapter 5, Even Easier Scraping
Chapter 6, Graph Construction and Cleaning

The rest of the chapter is locked

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

Table of Contents (17) Chapters

Part 2: Graph Construction and Cleanup

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Authors (1)