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Data Science for Web3

You're reading from   Data Science for Web3 A comprehensive guide to decoding blockchain data with data analysis basics and machine learning cases

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Product type Paperback
Published in Dec 2023
Publisher Packt
ISBN-13 9781837637546
Length 344 pages
Edition 1st Edition
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Concepts
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Author (1):
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Gabriela Castillo Areco Gabriela Castillo Areco
Author Profile Icon Gabriela Castillo Areco
Gabriela Castillo Areco
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Table of Contents (23) Chapters Close

Preface 1. Part 1 Web3 Data Analysis Basics
2. Chapter 1: Where Data and Web3 Meet FREE CHAPTER 3. Chapter 2: Working with On-Chain Data 4. Chapter 3: Working with Off-Chain Data 5. Chapter 4: Exploring the Digital Uniqueness of NFTs – Games, Art, and Identity 6. Chapter 5: Exploring Analytics on DeFi 7. Part 2 Web3 Machine Learning Cases
8. Chapter 6: Preparing and Exploring Our Data 9. Chapter 7: A Primer on Machine Learning and Deep Learning 10. Chapter 8: Sentiment Analysis – NLP and Crypto News 11. Chapter 9: Generative Art for NFTs 12. Chapter 10: A Primer on Security and Fraud Detection 13. Chapter 11: Price Prediction with Time Series 14. Chapter 12: Marketing Discovery with Graphs 15. Part 3 Appendix
16. Chapter 13: Building Experience with Crypto Data – BUIDL 17. Chapter 14: Interviews with Web3 Data Leaders 18. Index 19. Other Books You May Enjoy Appendix 1
1. Appendix 2
2. Appendix 3

Further reading

To learn more about the topics that were covered in this chapter, take a look at the following resources:

  • Introduction:
    • Bird, Steven, Edward Loper and Ewan Klein (2009), Natural Language Processing with Python. O’Reilly Media Inc. Available athttps://www.nltk.org/book/.
    • Yordanov, V. (2019, August 13). Introduction to natural language processing for text. Medium. Available at https://towardsdatascience.com/introduction-to-natural-language-processing-for-text-df845750fb63.
    • Gabriel Doyle, and Charles Elkan. (n.d.). Financial Topic Models. Available at https://pages.ucsd.edu/~gdoyle/papers/doyle-elkan-2009-nips-paper.pdf.
    • Sigmoider. (2018, May 3). Get started with NLP (Part I). Medium. Available at https://medium.com/@gon.esbuyo/get-started-with-nlp-part-i-d67ca26cc828.
    • Suhyeon Kim, Haecheong Park, and Junghye Lee. (n.d.). Word2vec-based latent semantic analysis (W2V-LSA) for topic modeling: A study on blockchain technology trend analysis. Available at https...
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