This is the code repository for Data Science for Web3, published by Packt.
A comprehensive guide to decoding blockchain data with data analysis basics and machine learning cases
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.
This book covers the following exciting features:
- Understand the core components of blockchain transactions and blocks
- Identify reliable sources of on-chain and off-chain data to build robust datasets
- Understand key Web3 business questions and how data science can offer solutions
- Build your skills to create and query NFT- and DeFi-specific datasets
- Implement a machine learning toolbox with real-world use cases in the Web3 space
If you feel this book is for you, get your copy today!
All of the code is organized into folders.
The code will look like the following:
{
'domain': {'id': '131', 'name': 'Unified Twitter Taxonomy', 'description': 'A taxonomy of user interests. '},
'entity': {'id': '913142676819648512', 'name': 'Cryptocurrencies', 'description': 'Cryptocurrency'}
},
Following is what you need for this book: This book is designed for data professionals—data analysts, data scientists, or data engineers— and business professionals, aiming to acquire the skills for extracting data from the Web3 ecosystem, as it demonstrates how to effectively leverage data tools for in-depth analysis of blockchain transactional data. If you seek hands-on experience, you'll find value in the shared repository, enabling you to experiment with the provided solutions. While not mandatory, a basic understanding of statistics, machine learning, and Python will enhance your learning experience.
With the following software and hardware list you can run all code files present in the book (Chapter 1-14).
| Chapter | Software required | OS required |
|---|---|---|
| 1-14 | Python 3.7+ | Any OS |
| 1-14 | Google Colaboratory or Jupyter notebook | Any OS |
Gabriela Castillo Areco holds an M. Sc. in Big Data Science from TECNUM School of Engineering, University of Navarra. Gabriela has undertaken roles as data scientist, machine learning analyst, and blockchain consultant in both large corporations and small ventures. She served as professor of "New Crypto Businesses" at Di Tella University and is currently a member of the BizOps data team at IOV Labs.