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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

Product type Paperback

Published in Dec 2023

Publisher Packt

ISBN-13 9781837637546

Length 344 pages

Edition 1st Edition

Languages

Python

Tools

Blockchain

Concepts

Blockchain

Author (1):

Gabriela Castillo Areco

View More author details

Table of Contents (23) Chapters

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

Why subscribe?

19. Other Books You May Enjoy

Appendix 1

1. Appendix 2

2. Appendix 3

Technical requirements

The technical requirements listed in Chapter 4 also apply to this chapter. We will be using indexed data available in SQL table services like Dune Analytics, Increment, and Flipside. To follow along, please open an account on any of these platforms by following the links provided in Chapter 2. Transactional data is queried with SQL services, and the syntax varies, depending on the query engines.

You can find Jupyter notebooks containing the examples discussed in this chapter in this book’s GitHub repository at https://github.com/PacktPublishing/Data-Science-for-Web3/tree/main/Chapter05. We recommend reading through the code files in the Chapter05 folder to follow along.

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Authors (1)

Gabriela Castillo Areco

Gabriela Castillo Areco

Gabriela Castillo Areco holds an M.Sc. in big data science from the TECNUM School of Engineering, University of Navarra. With extensive experience in both the business and data facets of blockchain technology, Gabriela has undertaken roles as a data scientist, machine learning analyst, and blockchain consultant in both large corporations and small ventures. She served as a professor of new crypto businesses at Torcuato di Tella University and is currently a member of the BizOps data team at IOV Labs.

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