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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

Generative Art for NFTs

“I use data as a pigment and paint with a painting brush that is assisted by artificial intelligence.”

– Refik Anadol

In this chapter, we’ll take an artistic break and indulge in some creativity. While our previous focus was on analyzing content generated by others on the blockchain, in this chapter, we will be creating our own content to be added to the blockchain.

The inclusion of this chapter stems from the recognition that, as data scientists, we might encounter requests to produce or assist in crafting an NFT collection in collaboration with a group of artists. In Chapter 4, we studied the artistic applications of NFTs and explored notable collections, such as Bored Ape, which has a total traded volume of 978,382 ETH (approximately USD 1,800 million). We do not know whether they used AI to produce all the images, but they are a good use case of how art can be owned and traded on the blockchain. To be able to participate...

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Data Science for Web3
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