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  • Book Overview & Buying Data Science for Web3
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Data Science for Web3

Data Science for Web3

By : Gabriela Castillo Areco
5 (3)
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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

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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Data Science for Web3
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