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Data Science for Web3

You're reading from   Data Science for Web3 A comprehensive guide to decoding blockchain data with data analysis basics and machine learning cases

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Product type Paperback
Published in Dec 2023
Publisher Packt
ISBN-13 9781837637546
Length 344 pages
Edition 1st Edition
Languages
Concepts
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Author (1):
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Gabriela Castillo Areco Gabriela Castillo Areco
Author Profile Icon Gabriela Castillo Areco
Gabriela Castillo Areco
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Table of Contents (23) Chapters Close

Preface 1. Part 1 Web3 Data Analysis Basics
2. Chapter 1: Where Data and Web3 Meet FREE CHAPTER 3. Chapter 2: Working with On-Chain Data 4. Chapter 3: Working with Off-Chain Data 5. Chapter 4: Exploring the Digital Uniqueness of NFTs – Games, Art, and Identity 6. Chapter 5: Exploring Analytics on DeFi 7. Part 2 Web3 Machine Learning Cases
8. Chapter 6: Preparing and Exploring Our Data 9. Chapter 7: A Primer on Machine Learning and Deep Learning 10. Chapter 8: Sentiment Analysis – NLP and Crypto News 11. Chapter 9: Generative Art for NFTs 12. Chapter 10: A Primer on Security and Fraud Detection 13. Chapter 11: Price Prediction with Time Series 14. Chapter 12: Marketing Discovery with Graphs 15. Part 3 Appendix
16. Chapter 13: Building Experience with Crypto Data – BUIDL 17. Chapter 14: Interviews with Web3 Data Leaders 18. Index 19. Other Books You May Enjoy Appendix 1
1. Appendix 2
2. Appendix 3

A primer on graphs

According to Innar Liiv, “Network science, sometimes considered a subfield of data science and sometimes an independent academic field, is a set of techniques, methods, and tools to study patterns in networked structures.” An example of a network is the image of the London underground map:

Figure 12.1 – An overview of Beck’s design for the London underground map (source: https://en.wikipedia.org/wiki/File:Beck_Map_1933.jpg found under fair use)

Figure 12.1 – An overview of Beck’s design for the London underground map (source: https://en.wikipedia.org/wiki/File:Beck_Map_1933.jpg found under fair use)

In our exploration of networks and graphs, we will use these terms interchangeably.

The study of networks has gained significant interest in recent years due to their ability to explain relationships between entities simply. As explained by Professor Matías Avila, “A network, also called a graph in the mathematical literature, is a collection of nodes where some pairs are connected by edges.

In this primer, we will explore fundamental concepts...

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