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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

Summary

In conclusion, this chapter delved into the world of on-chain data, which serves as the primary data source in Web3. We started the chapter by dissecting individual transactions and gaining insights into their structure and components. This understanding was further expanded as we explored the anatomy of blocks.

Moving forward, we delved into an analysis of state data. By examining state variables and their significance, we gained a deeper understanding of how data is stored and accessed within a blockchain.

To further enhance our ability to work with on-chain data, we explored a range of data providers. From widely used block explorers such as Etherscan to powerful APIs such as Infura, Moralis, and Covalent, and SQL-accessible tables such us Dune and Flipside, we built a comprehensive list of resources that grant us access to on-chain data. Each provider offers unique features, data formats, and querying capabilities, allowing us to tailor our approach based on the specific...

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Data Science for Web3
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