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Graph Machine Learning

You're reading from   Graph Machine Learning Take graph data to the next level by applying machine learning techniques and algorithms

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Product type Paperback
Published in Jun 2021
Publisher Packt
ISBN-13 9781800204492
Length 338 pages
Edition 1st Edition
Languages
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Authors (3):
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Aldo Marzullo Aldo Marzullo
Author Profile Icon Aldo Marzullo
Aldo Marzullo
Claudio Stamile Claudio Stamile
Author Profile Icon Claudio Stamile
Claudio Stamile
Enrico Deusebio Enrico Deusebio
Author Profile Icon Enrico Deusebio
Enrico Deusebio
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Toc

Table of Contents (15) Chapters Close

Preface 1. Section 1 – Introduction to Graph Machine Learning
2. Chapter 1: Getting Started with Graphs FREE CHAPTER 3. Chapter 2: Graph Machine Learning 4. Section 2 – Machine Learning on Graphs
5. Chapter 3: Unsupervised Graph Learning 6. Chapter 4: Supervised Graph Learning 7. Chapter 5: Problems with Machine Learning on Graphs 8. Section 3 – Advanced Applications of Graph Machine Learning
9. Chapter 6: Social Network Graphs 10. Chapter 7: Text Analytics and Natural Language Processing Using Graphs 11. Chapter 8:Graph Analysis for Credit Card Transactions 12. Chapter 9: Building a Data-Driven Graph-Powered Application 13. Chapter 10: Novel Trends on Graphs 14. Other Books You May Enjoy

Section 1 – Introduction to Graph Machine Learning

In this section, the reader will get a brief introduction to graph machine learning, showing the potential of graphs combined with the right machine learning algorithms. Moreover, a general overview of graph theory and Python libraries is provided in order to allow the reader to deal with (that is, create, modify, and plot) graph data structures.

This section comprises the following chapters:

  • Chapter 1, Getting Started with Graphs
  • Chapter 2, Graph Machine Learning
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