Issue #221
October 25, 2023
This week’s Data Science Book, "SQL for Data Analysis: Advanced Techniques for Transforming Data into Insights" by Cathy Tanimura. This book is a must-have resource for anyone serious about data analysis and SQL. It equips you with the tools and knowledge to tackle complex data analysis tasks with confidence. With its clear explanations, real-world examples, and comprehensive coverage of advanced topics, this book will undoubtedly become an invaluable asset in your data analysis journey. Whether you're a data analyst, data scientist, or a SQL enthusiast, this book will help you take your skills to the next level and transform data into actionable insights.
- 1. Generative AI exists because of the transformer [ig.ft.com]
- 2. Causal inference as a blind spot of data scientists [dzidas.com]
- 3. OpenAI Finally Allows ChatGPT Complete Internet Access [gizmodo.com]
- 4. What Every Developer Should Know About GPU Computing [codeconfessions.substack.com]
- 5. The conditional query fallacy: Applying Bayesian inference from discrete mathematics perspective [science-memo.blogspot.com]
- 6. Accounting for Computer Scientists [martin.kleppmann.com]
- 7. The Foundation Model Transparency Index [crfm.stanford.edu]
- • An AI revolution is brewing in medicine. What will it look like? (M. Lenharo)
- • Living guidelines for generative AI — why scientists must oversee its use (C. L. Bockting, E. A. M. van Dis, R. van Rooij, W. Zuidema, J. Bollen)
- • Bayesian inference of transition matrices from incomplete graph data with a topological prior (V. Perri, L. V. Petrović, I. Scholtes)
- • The Complex Network Patterns of Human Migration at Different Geographical Scales: Network Science meets Regression Analysis (D. Pitoski, A. Meštrović, H. Schmeets)
- • Reconstruction of multiplex networks via graph embeddings (D. Kaiser, S. Patwardhan, M. Kim, F. Radicchi)
- • Networked Inequality: Preferential Attachment Bias in Graph Neural Network Link Prediction (A. Subramonian, L. Sagun, Y. Sun)
- • Deeper but smaller: Higher-order interactions increase linear stability but shrink basins (Y. Zhang, P. S. Skardal, F. Battiston, G. Petri, M. Lucas)
Why Isn't Functional Programming the Norm?
All our videos are also available in our YouTube playlist.
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