Issue #174

September 25, 2022

This weeks Data Science Book is " Fundamentals of Data Engineering " by J. Reis and M. Housley. While our focus is on Data Science, we can't downplay the major role played by Data Engineering in practical Data projects. In this recent tome, the authors guide us through the thought processes, concepts and principles necessary to establish a successful Data Engineering operation to help support all of your data driven projects. They recommend a cloud first approach that allows for quick experimentation, adaptation and scaling.

Fundamentals of Data Engineering

1. Decision Trees From Scratch With Python [opendatascience.com]
2. Web Scraping with Python – A Step by Step Guide [scrapingdog.com]
3. How to build TRUST in Machine Learning, the sane way [medium.com/bigabids-dataverse]
4. How Complex Systems Fail [how.complexsystems.fail]
5. What to read to become a better writer [economist.com]
6. Machine Learning for Fraud Detection in Streaming Services [netflixtechblog.medium.com]
7. 10 Mental Models for Learning Anything [scotthyoung.medium.com]
8. Think About the Law of Large Numbers Horizontally, Not Just Vertically [medium.com/geekculture]

• Weak ties, failed tries, and success (D. Wang, B. Uzzi)
• Identifying Top-N Influential Nodes in Large Complex Networks Using Network Structure (M. Venunath, P. Sujatha, P. Koti)
• Link Prediction of Complex Network Based on Eigenvector Centrality (L. Wang, C. Chen, H. Li)
• The Beginning of the Monte-Carlo Method (N. Metropolis)
• Basic reproduction number of epidemic models on sparse networks (S. Morita)
• Link prediction in complex networks based on communication capacity and local paths (J. Peng, G. Xu, X. Zhou, C. Dong, L. Meng)
• Counteracting Filter Bubbles with Homophily-Aware Link Recommendations (R. Warton, C. Volny, K. S. Xu)

All the videos of the week are now available in ourYoutube playlist.

September 25, 2022

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