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Welcome to the 253rd edition of the Data Science Briefing!
We're proud to announce that the next edition of the Generative Artificial Intelligence with the OpenAI API for Developers webinar has just been scheduled for Oct 9th. Register now so you don't miss out! Also, the next edition of the ChatGPT and Competing LLMs webinar is coming up in less than a week on Aug 13th. Registrations are still open, so Register now to secure your spot.
The most recent post on the Epidemiology series, Epidemiology 303: Metapopulation Models, explores how to connect multiple populations through a travel matrix. In the graph subsection, you'll find all you need to know about k-core Decomposition, while in the Visualization section, you can explore The Effects of Vaccination through a WSJ visualization.
In our regularly scheduled content, we explore how Artificial Intelligence Gives Weather Forecasters a New Edge, learn how to write a tile server in python, Try Kolmogorov-Arnold Networks in Practice and dive into The Truth About Linear Regression.
On the academic front, we learn the consequences of generative AI for online knowledge communities, explore Knowledge Graphs and Empirically measure online social influence.
This week's book recommendation is "Working with Network Data" by J. Bagrow and Y.-Y. Ahn. You can find all the previous book recommendations on our website. In this week's video, we have a lecture on the Physics of Language Models: Knowledge Storage, Extraction, and Manipulation.
Data shows that the best way for a newsletter to grow is by word of mouth, so if you think one of your friends or colleagues would enjoy this newsletter, go ahead and forward this email to them. This will help us spread the word!
Semper discentes,
The D4S Team
This week's book is "Working with Network Data" by J. Bagrow and Y.-Y. Ahn. Networks are the keystone concept necessary to understand a wealth of real-world complex systems whose behavior is characterized by interactions between individual components. In this book, J. Bagrow and Y.-Y. Ahn, two leading researchers in the field of Complex Networks, introduce readers to the fundamental concepts of Network Science and how to apply them to practical datasets. Their hands-on approach will get you up to speed quickly, allowing you to develop effective approaches to understanding your own network datasets.
- Artificial Intelligence Gives Weather Forecasters a New Edge [nytimes.com]
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Introducing GitHub Models: A new generation of AI engineers building on GitHub [github.blog]
- Writing a tile server in python [grulic.org.ar]
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Trying Kolmogorov-Arnold Networks in Practice [cprimozic.net]
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A Visual Guide to Quantization [newsletter.maartengrootendorst.com]
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Why many studies wrongly claim it’s healthy to drink a little alcohol [newscientist.com]
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The Truth About Linear Regression [stat.cmu.edu]
- Spatial scales of COVID-19 transmission in Mexico (B. Klein, H. Hartle, M. Shrestha, A. C. Zenteno, D. B. S. Cordera, J. R. Nicolás-Carlock, A. I. Bento, B. M. Althouse, B. Gutierrez, M. Escalera-Zamudio, A. Reyes-Sandoval, O. G. Pybus, A. Vespignani, J, A. D. Quiñonez, S. V. Scarpino, M. U. G. Kraemer)
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The consequences of generative AI for online knowledge communities (G. Burtch, D. Lee, Z. Chen)
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Knowledge Graphs (C. Gutierrez, J. F. Sequeda)
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Empirically measuring online social influence (R. Ram, M.-A. Rizoiu)
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D-Bot: Database Diagnosis System using Large Language Models (X. Zhou, G. Li, Z. Sun, Z. Liu, W. Chen, J. Wu, J. Liu, R. Feng, G. Zeng)
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KAN or MLP: A Fairer Comparison (R. Yu, W. Yu, X. Wang)
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Rate of epidemic spreading on complex networks (S. Cure, F. G. Pflug, S. Pigolotti)
Physics of Language Models: Knowledge Storage, Extraction, and Manipulation
 All the videos of the week are now available in our Youtube playlist.
Upcoming Events:
Opportunities to learn from us
On-Demand Videos:
Long-form tutorials
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