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Data Science for Web3

Data Science for Web3

By : Gabriela Castillo Areco
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Data Science for Web3

Data Science for Web3

5 (3)
By: Gabriela Castillo Areco

Overview of this book

Data is the new oil and Web3 is generating it at an unprecedented rate. Complete with practical examples, detailed explanations, and ideas for portfolio development, this comprehensive book serves as a step-by-step guide covering the industry best practices, tools, and resources needed to easily navigate the world of data in Web3. You’ll begin by acquiring a solid understanding of key blockchain concepts and the fundamental data science tools essential for Web3 projects. The subsequent chapters will help you explore the main data sources that can help address industry challenges, decode smart contracts, and build DeFi- and NFT-specific datasets. You’ll then tackle the complexities of feature engineering specific to blockchain data and familiarize yourself with diverse machine learning use cases that leverage Web3 data. The book includes interviews with industry leaders providing insights into their professional journeys to drive innovation in the Web 3 environment. Equipped with experience in handling crypto data, you’ll be able to demonstrate your skills in job interviews, academic pursuits, or when engaging potential clients. By the end of this book, you’ll have the essential tools to undertake end-to-end data science projects utilizing blockchain data, empowering you to help shape the next-generation internet.
Table of Contents (23 chapters)
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1
Part 1 Web3 Data Analysis Basics
7
Part 2 Web3 Machine Learning Cases
15
Part 3 Appendix
1
Appendix 1
2
Appendix 2
3
Appendix 3

Working with Off-Chain Data

In the previous chapter, we learned that on-chain data serves as the primary source of Web3 data analysis. It is open, distributed, and trustworthy. While on-chain data will be key to answering most business data science questions, it is essential to complement it with relevant information from off-chain data sources, which is the focus of this chapter.

Consider a scenario where we receive a request to assess the economic relevance of a smart contract. We can query the number of tokens locked in it, but to finalize the analysis, we need to determine the monetary value of those tokens. To accomplish this, we must integrate on-chain data with prices, often derived from off-chain sources.

Prices, news, and opinions are not stored on-chain and must be retrieved from external sources. In this chapter, we will delve into those sources and acquire data from selected APIs. Specifically, we will discuss alternatives for fetching prices, analyze a crypto news...

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Data Science for Web3
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