Data Science for Web3 A Comprehensive Guide to Decoding Blockchain Data with Data Analysis Basics and Machine Learning Cases
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...
| Otros Autores: | , |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Birmingham :
Packt Publishing, Limited
2023.
Birmingham, England : [2023] |
| Edición: | First edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009827937706719 |
Tabla de Contenidos:
- 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
- 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
- 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
- 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
- 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
- Summary
- Further reading
- Chapter 7: A Primer on Machine Learning and Deep Learning
- Technical requirements
- 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
- Summary
- Further reading
- Chapter 8: Sentiment Analysis - NLP and Crypto News
- Technical requirements
- Example datasets
- Building our pipeline
- Preparation
- Model building
- Training and evaluation
- ChatGPT integration
- Summary
- Further reading
- Chapter 9: Generative Art for NFTs
- Technical requirements
- Creating with colors - colorizing
- Hands-on Style2Paints.
- Theory
- A note on training datasets
- Creating with style - style transfer
- Preparation
- Model building
- Training and inference
- Creating with prompts - text to image
- DALL.E 2
- Stable Diffusion
- Midjourney
- Leonardo.Ai
- Minting an NFT collection
- Summary
- Further reading
- Chapter 10: A Primer on Security and Fraud Detection
- Technical requirements
- A primer on illicit activity on Ethereum
- Preprocessing
- Training the model
- Evaluating the results
- Presenting results
- Summary
- Further reading
- Chapter 11: Price Prediction with Time Series
- Technical requirements
- A primer on time series
- Exploring the dataset
- Discussing traditional pipelines
- Preprocessing
- Modeling - ARIMA/SARIMAX and Auto ARIMA
- Auto ARIMA
- Adding exogenous variables
- Using a neural network - LSTM
- Preprocessing
- Model building
- Training and evaluation
- Summary
- Further reading
- Chapter 12: Marketing Discovery with Graphs
- Technical requirements
- A primer on graphs
- Types of graphs
- Graph properties
- The dataset
- Node classification
- Preparation
- Modeling
- Training and evaluation
- Summary
- Further reading
- 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
- Summary
- Further reading
- 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.
