Data Science for Web3 : A Comprehensive Guide to Decoding Blockchain Data with Data Analysis Basics and Machine Learning Cases / Gabriela Castillo Areco.

Format:

Book

Author/Creator:

Areco, Gabriela Castillo, author.

Contributor:

Dahlquist, José, writer of foreword.

Language:

English

Subjects (All):

World Wide Web--Technological innovations.

World Wide Web.

Business--Data processing.

Business.

Blockchains (Databases)--Industrial applications.

Blockchains (Databases).

Cryptocurrencies.

Web applications.

Physical Description:

1 online resource (344 pages)

Edition:

First edition.

Place of Publication:

Birmingham : Packt Publishing, Limited, 2023.

Birmingham, England : Packt Publishing Ltd., [2023]

Summary:

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.

Contents:

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

NFT Floor Price

The concept of "lost"

A brief overview of APIs

Summary

Further reading

Chapter 2: Working with On-Chain Data

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

Chapter 3: Working with Off-Chain Data

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)

Chapter 4: Exploring the Digital Uniqueness of NFTs - Games, Art, and Identity

Enabling unique asset tracking on the blockchain using NFT

The business requests

The technical solution

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

Data extraction

Floor price and wash trading

A word on anti-money laundering (AML) practices

Chapter 5: Exploring Analytics on DeFi

Stablecoins and other tokens

Understanding tokens, native assets, and the ERC-20 data structure

Hands-on example

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

Part 2 Web3 Machine Learning Cases

Chapter 6: Preparing and Exploring Our Data

Data preparation

Hex values

Checksum

Decimal treatment

From Unix timestamps to datetime formats

Evolution of smart contracts

Exploratory Data Analysis

Summarizing data

Outlier detection

Chapter 7: A Primer on Machine Learning and Deep Learning

Introducing machine learning

Building a machine learning pipeline

Model

Training

Underfitting and overfitting

Prediction and evaluation

Introducing deep learning

Model preparation

Model building

Training and evaluating a model

Chapter 8: Sentiment Analysis - NLP and Crypto News

Example datasets

Building our pipeline

Preparation

Training and evaluation

ChatGPT integration

Chapter 9: Generative Art for NFTs

Creating with colors - colorizing

Hands-on Style2Paints.

Theory

A note on training datasets

Creating with style - style transfer

Training and inference

Creating with prompts - text to image

DALL.E 2

Stable Diffusion

Midjourney

Leonardo.Ai

Minting an NFT collection

Chapter 10: A Primer on Security and Fraud Detection

A primer on illicit activity on Ethereum

Preprocessing

Training the model

Evaluating the results

Presenting results

Chapter 11: Price Prediction with Time Series

A primer on time series

Exploring the dataset

Discussing traditional pipelines

Modeling - ARIMA/SARIMAX and Auto ARIMA

Auto ARIMA

Adding exogenous variables

Using a neural network - LSTM

Chapter 12: Marketing Discovery with Graphs

A primer on graphs

Types of graphs

Graph properties

The dataset

Node classification

Modeling

Part 3 Appendix

Chapter 13: Building Experience with Crypto Data - BUIDL

Showcasing your work - portfolio

Looking for a job

Preparing for a job interview

Importance of soft skills

Where to study

Chapter 14: Interviews with Web3 Data Leaders

Hildebert Moulié (aka hildobby)

Jackie Zhang

Marina Ghosh

Professor One Digit

Appendix 1

Appendix 2

Appendix 3

Index

Other Books You May Enjoy.

Notes:

Includes index.

Description based on print version record.

Other Format:

Print version: Areco, Gabriela Castillo Data Science for Web3

ISBN:

9781837635580

1837635587

OCLC:

1416747483