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Data Science for Web3

You're reading from Data Science for Web3

Product type Book

Published in Dec 2023

Publisher Packt

ISBN-13 9781837637546

Pages 344 pages

Edition 1st Edition

Languages

Concepts

Author (1):

Gabriela Castillo Areco

Table of Contents (23) Chapters

Preface

Part 1 Web3 Data Analysis Basics

Chapter 1: Where Data and Web3 Meet

Chapter 2: Working with On-Chain Data

Chapter 3: Working with Off-Chain Data

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

Chapter 5: Exploring Analytics on DeFi

Part 2 Web3 Machine Learning Cases

Chapter 6: Preparing and Exploring Our Data

Chapter 7: A Primer on Machine Learning and Deep Learning

Chapter 8: Sentiment Analysis – NLP and Crypto News

Chapter 9: Generative Art for NFTs

Chapter 10: A Primer on Security and Fraud Detection

Chapter 11: Price Prediction with Time Series

Chapter 12: Marketing Discovery with Graphs

Part 3 Appendix

Chapter 13: Building Experience with Crypto Data – BUIDL

Chapter 14: Interviews with Web3 Data Leaders

Index

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Other Books You May Enjoy

Appendix 1

Appendix 2

Appendix 3

Further reading

To complement this chapter, the following links may help:

Time Series Analysis in R Part 2: Time Series Transformations. (n.d.). An online community for showcasing R & Python tutorials. DataScience+. https://datascienceplus.com/time-series-analysis-in-r-part-2-time-series-transformations/
Computer Science. (2019, December 22). Stock Price Prediction Using Python & Machine Learning [Video]. YouTube. https://www.youtube.com/watch?v=QIUxPv5PJOY
Luis Alberiko Gil-Alaña. (2021). Introduction to Time Series [PDF document].
Cryptocurrencies and stock market indices. Are they related? LA Gil-Alaña, EJA Abakah, MFR Rojo. Research in International Business and Finance, 2020. http://ddfv.ufv.es/bitstream/handle/10641/2229/cryptocurrencies%20and%20stock%20market%20indices.pdf?sequence=1&isAllowed=y
Modelling long memory volatility in the Bitcoin market: Evidence of persistence and structural breaks. E Bouri, LA Gil-Alaña, R Gupta...

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Authors (1)

Gabriela Castillo Areco

Gabriela Castillo Areco holds an M.Sc. in big data science from the TECNUM School of Engineering, University of Navarra. With extensive experience in both the business and data facets of blockchain technology, Gabriela has undertaken roles as a data scientist, machine learning analyst, and blockchain consultant in both large corporations and small ventures. She served as a professor of new crypto businesses at Torcuato di Tella University and is currently a member of the BizOps data team at IOV Labs.

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