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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
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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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Toc

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

Technical requirements

In this chapter, we will extensively utilize the requests library. This popular and user-friendly Python library simplifies the process of sending HTTP requests and handling responses. HTTP requests form the foundation of client-server communication in web applications and APIs, enabling clients to request specific resources or perform actions on the server, such as data retrieval, creation, modification, and deletion.

If you haven’t installed requests yet, you can do so by executing the following command:

pip install requests

The documentation for requests is available at the following link: https://requests.readthedocs.io/en/latest/.

You can find all the data and code files for this chapter in the book’s GitHub repository, accessible here: https://github.com/PacktPublishing/Data-Science-for-Web3/tree/main/Chapter02.

We recommend that you read through the code files in the Chapter02 folder to follow along with the chapter.

A note...

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