Data Science for Web3 A Comprehensive Guide to Decoding Blockchain Data with Data Analysis Basics and Machine Learning Cases
Author
Published
Birmingham : Packt Publishing, Limited, 2023.
Status
Available Online
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Language
English
ISBN
1837635587, 9781837635580
Notes
General Note
Description based upon print version of record.
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Summary
Description
Be part of the future of Web3, decoding blockchain data to build trust in the next-generation internet Key Features Build a deep understanding of the fundamentals of blockchain analytics Extract actionable business insights by modeling blockchain data Showcase your work and gain valuable experience to seize opportunities in the Web3 ecosystem Purchase of the print or Kindle book includes a free PDF eBook Book Description 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. What you will learn 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 Who this book is for 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.
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O'Reilly O'Reilly Online Learning: Academic/Public Library Edition
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Citations
APA Citation, 7th Edition (style guide)
Areco, G. C., & Dahlquist, J. (2023). Data Science for Web3: A Comprehensive Guide to Decoding Blockchain Data with Data Analysis Basics and Machine Learning Cases . Packt Publishing, Limited.
Chicago / Turabian - Author Date Citation, 17th Edition (style guide)Areco, Gabriela Castillo and José, Dahlquist. 2023. Data Science for Web3: A Comprehensive Guide to Decoding Blockchain Data With Data Analysis Basics and Machine Learning Cases. Birmingham: Packt Publishing, Limited.
Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)Areco, Gabriela Castillo and José, Dahlquist. Data Science for Web3: A Comprehensive Guide to Decoding Blockchain Data With Data Analysis Basics and Machine Learning Cases Birmingham: Packt Publishing, Limited, 2023.
Harvard Citation (style guide)Areco, G. C. and Dahlquist, J. (2023). Data science for web3: a comprehensive guide to decoding blockchain data with data analysis basics and machine learning cases. Birmingham: Packt Publishing, Limited.
MLA Citation, 9th Edition (style guide)Areco, Gabriela Castillo,, and José Dahlquist. Data Science for Web3: A Comprehensive Guide to Decoding Blockchain Data With Data Analysis Basics and Machine Learning Cases Packt Publishing, Limited, 2023.
Note! Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy. Citation formats are based on standards as of August 2021.
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Grouped Work ID
fa404f5a-70fa-93fa-f083-07883203a2d8-eng
Grouping Information
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| Full title | data science for web3 a comprehensive guide to decoding blockchain data with data analysis basics and machine learning cases |
| Author | areco gabriela castillo |
| Grouping Category | book |
| Last Update | 2025-01-24 12:33:29PM |
| Last Indexed | 2025-02-27 03:49:01AM |
Book Cover Information
| Image Source | google_isbn |
|---|---|
| First Loaded | Dec 23, 2024 |
| Last Used | Mar 3, 2025 |
Marc Record
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| Last File Modification Time | Dec 17, 2024 08:28:56 AM |
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| 100 | 1 | |a Areco, Gabriela Castillo,|e author. | |
| 245 | 1 | 0 | |a Data Science for Web3|h [electronic resource] :|b A Comprehensive Guide to Decoding Blockchain Data with Data Analysis Basics and Machine Learning Cases /|c Gabriela Castillo Areco ; foreword by José Dahlquist. |
| 260 | |a Birmingham :|b Packt Publishing, Limited,|c 2023. | ||
| 300 | |a 1 online resource (344 p.) | ||
| 500 | |a Description based upon print version of record. | ||
| 500 | |a Summary | ||
| 505 | 0 | |a Cover -- Title Page -- Copyright and Credits -- Foreword -- Contributors -- Table of Contents -- Preface -- Part 1 Web3 Data Analysis Basics -- Chapter 1: Where Data and Web3 Meet -- Technical requirements -- Exploring the data ingredients -- Understanding the blockchain ingredients -- Three generations of blockchain -- Introducing the blockchain ingredients -- Making the first transaction -- Approaching Web3 industry metrics -- Block height -- Time -- Tokenomics -- Total Value Locked (TVL) -- Total market cap -- Data quality challenges -- Data standards challenges -- Retail -- Confirmations | |
| 505 | 8 | |a NFT Floor Price -- The concept of "lost" -- A brief overview of APIs -- Summary -- Further reading -- Chapter 2: Working with On-Chain Data -- Technical requirements -- Dissecting a transaction -- Nonce -- Gas price -- Gas limit -- Recipient -- Sender -- Value -- Input data -- V,R,S -- Transaction receipt -- Status -- Gas used and Cumulative gas used -- Logs -- Dissecting a block -- Exploring state data -- Reviewing data sources -- Block explorers -- Infura -- Moralis -- GetBlock -- Dune -- Covalent -- Flipside -- The Graph -- Google BigQuery -- Summary -- Further reading | |
| 505 | 8 | |a Chapter 3: Working with Off-Chain Data -- Technical requirements -- Introductory example -- listing data sources -- Adding prices to our dataset -- CoinGecko -- CoinMarketCap -- Binance -- Oracles -- Chainlink -- OHLC -- Kraken -- Final thoughts on prices -- Adding news to our dataset -- Adding social networks to our dataset -- X (formerly Twitter) -- Summary -- Further reading -- Chapter 4: Exploring the Digital Uniqueness of NFTs -- Games, Art, and Identity -- Technical requirements -- Enabling unique asset tracking on the blockchain using NFT -- The business requests -- The technical solution | |
| 505 | 8 | |a Blockchain gaming -- the GameFi proposal -- Introduction to the business landscape -- Analytics -- Identity in the blockchain -- Introduction to the business landscape -- Analytics -- Redefining the art business with blockchain -- Introduction to the business landscape -- Data extraction -- Floor price and wash trading -- A word on anti-money laundering (AML) practices -- Summary -- Further reading -- Chapter 5: Exploring Analytics on DeFi -- Technical requirements -- Stablecoins and other tokens -- Understanding tokens, native assets, and the ERC-20 data structure -- Hands-on example | |
| 505 | 8 | |a Understanding DEX -- Hands-on example -- pools and AMM -- DEX aggregators -- Lending and borrowing services on Web3 -- Flash loans -- A note on protocol bad debt -- Multichain protocols and cross-chain bridges -- Hands-on example -- Hop bridge -- Summary -- Further reading -- Part 2 Web3 Machine Learning Cases -- Chapter 6: Preparing and Exploring Our Data -- Technical requirements -- Data preparation -- Hex values -- Checksum -- Decimal treatment -- From Unix timestamps to datetime formats -- Evolution of smart contracts -- Exploratory Data Analysis -- Summarizing data -- Outlier detection | |
| 520 | |a Be part of the future of Web3, decoding blockchain data to build trust in the next-generation internet Key Features Build a deep understanding of the fundamentals of blockchain analytics Extract actionable business insights by modeling blockchain data Showcase your work and gain valuable experience to seize opportunities in the Web3 ecosystem Purchase of the print or Kindle book includes a free PDF eBook Book Description 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. What you will learn 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 Who this book is for 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. | ||
| 590 | |a O'Reilly|b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a World Wide Web|x Technological innovations. | |
| 650 | 0 | |a Business|x Data processing.|9 31545 | |
| 650 | 0 | |a Blockchains (Databases)|x Industrial applications. | |
| 650 | 0 | |a Cryptocurrencies. | |
| 650 | 0 | |a Web applications.|9 403889 | |
| 700 | 1 | |a Dahlquist, José,|e writer of foreword. | |
| 776 | 0 | 8 | |i Print version:|a Areco, Gabriela Castillo|t Data Science for Web3|d Birmingham : Packt Publishing, Limited,c2023 |
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