Data Science for Web3: A comprehensive guide to decoding blockchain data with data analysis basics and machine learning cases
暫譯: Web3 數據科學:解碼區塊鏈數據的全面指南,包含數據分析基礎與機器學習案例
Areco, Gabriela Castillo
- 出版商: Packt Publishing
- 出版日期: 2023-12-29
- 售價: $1,860
- 貴賓價: 9.5 折 $1,767
- 語言: 英文
- 頁數: 344
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1837637547
- ISBN-13: 9781837637546
-
相關分類:
區塊鏈 Blockchain、Data Science、Machine Learning
海外代購書籍(需單獨結帳)
相關主題
商品描述
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.
商品描述(中文翻譯)
成為 Web3 未來的一部分,解碼區塊鏈數據以建立下一代互聯網的信任
主要特點:
- 深入理解區塊鏈分析的基本原理
- 通過建模區塊鏈數據提取可行的商業洞察
- 展示您的作品並獲得寶貴的經驗,以把握 Web3 生態系統中的機會
- 購買印刷版或 Kindle 書籍包括免費 PDF 電子書
書籍描述:
數據是新的石油,而 Web3 正以前所未有的速度生成數據。本書提供實用範例、詳細解釋和作品集開發的想法,作為一步步的指南,涵蓋了輕鬆導航 Web3 數據世界所需的行業最佳實踐、工具和資源。
您將首先獲得對區塊鏈關鍵概念和 Web3 項目所需的基本數據科學工具的堅實理解。隨後的章節將幫助您探索主要數據來源,以解決行業挑戰,解碼智能合約,並構建 DeFi 和 NFT 特定的數據集。然後,您將處理特定於區塊鏈數據的特徵工程的複雜性,並熟悉利用 Web3 數據的各種機器學習用例。
本書包括與行業領袖的訪談,提供他們在 Web3 環境中推動創新的職業旅程的見解。憑藉處理加密數據的經驗,您將能夠在求職面試、學術追求或與潛在客戶互動時展示您的技能。
在本書結束時,您將擁有利用區塊鏈數據進行端到端數據科學項目的基本工具,使您能夠幫助塑造下一代互聯網。
您將學到什麼:
- 理解區塊鏈交易和區塊的核心組件
- 識別可靠的鏈上和鏈下數據來源,以構建穩健的數據集
- 理解關鍵的 Web3 商業問題以及數據科學如何提供解決方案
- 提升您的技能以創建和查詢 NFT 和 DeFi 特定的數據集
- 在 Web3 領域實施具有現實世界用例的機器學習工具箱
本書適合誰:
本書旨在為數據專業人士——數據分析師、數據科學家或數據工程師——以及商業專業人士設計,旨在獲得從 Web3 生態系統中提取數據的技能,因為它展示了如何有效利用數據工具深入分析區塊鏈交易數據。如果您尋求實踐經驗,您將在共享的資源庫中找到價值,使您能夠實驗提供的解決方案。雖然不是必須的,但對統計學、機器學習和 Python 的基本理解將增強您的學習體驗。