Issue #276

April 2, 2025

Dear Reader,

Welcome to the April 2nd issue of the Data Science Briefing!

This week, we’re thrilled to share our latest blog post on the Data For Science Substack, where you can learn how to create Choropleth Maps using Shapefiles.

After the great success of the first edition, we’re happy to announce that you can already Register for the next edition of the Machine Learning with PyTorch for Developers webinar scheduled for Jun 4th. There are still a few open slots for next Wednesday’s NLP with PyTorch webinar, so go ahead and register so you don’t miss out!

This edition explores a diverse range of innovations in AI and developer tools. One highlight is the decision to use LangGraph for building a coding agent, emphasizing a commitment to more intelligent and streamlined development processes. Additionally, an insightful overview of the state of generative models charts the rapid advancements and future directions in synthetic content creation. Delving deeper into model behavior, another article offers a fascinating look at tracing the inner workings of a large language model, revealing the nuanced thought processes behind its outputs. Lastly, a practical guide on the matrix calculus essential for deep learning equips practitioners with the mathematical tools necessary to master complex neural networks.

Emerging research is revealing intricate connections between our environment, cognitive behavior, and data analytics. One study uncovers links between climate change and increased suicidal behavior risks, emphasizing how global warming might profoundly affect mental health. Meanwhile, investigations into habitual GPS use suggest that overreliance on digital navigation can impair spatial memory, subtly reshaping our cognitive landscape. Complementing these findings, innovative work leveraging existing fiber-optic networks for urban sensing is redefining real-time data collection, while critical analyses highlight how global population datasets may systematically underrepresent rural communities.

This week’s book is “The Complete Developer” by M. Krause. You can find all the previous book recommendations on our website. In this week’s video, we have a lecture on how You don’t know Git.

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Semper discentes,

The D4S Team

This week's book is "The Complete Developer" by M. Krause. This is a comprehensive guide that takes readers on a journey through the intricacies of modern full-stack web and API development. With over two decades of experience building websites and leading development teams, Krause offers an indispensable resource for developers at any career stage. The book covers various technologies, including TypeScript, React, Next.js, MongoDB, and Docker, providing a 360-degree view of web development.

One of the standout features of this book is its beginner-friendly approach, breaking down complex concepts into easy-to-follow steps. Krause meticulously covers every aspect of modern web application development, from building a React-driven frontend to constructing a robust backend using Mongoose and MongoDB, and integrating both REST and GraphQL APIs. The book is structured in two halves: one for demonstrating parts of the stack like React, Next.js, and Docker, and another for writing the final application and connecting the stack parts cohesively.

While some readers have found the material challenging for absolute beginners, many developers, including those with experience in other areas, have praised the book for its comprehensive coverage and practical approach. The inclusion of modern development practices and tools like Docker, Express.js, and OAuth for authentication sets readers up for real-world development scenarios. Despite the rapidly evolving nature of web technologies. "The Complete Developer" provides a solid foundation for mastering the modern full stack, making it a valuable resource for those looking to enhance their development skills with the latest Javascript based technologies.

The Complete Developer

1. Why we chose LangGraph to build our coding agent [qodo.ai]
2. The State of Generative Models [nrehiew.github.io]
3. How to Write Blog Posts that Developers Read [refactoringenglish.com]
4. Tracing the thoughts of a large language model [anthropic.com]
5. A (Long) Peek into Reinforcement Learning [lilianweng.github.io]
6. A machine learning library written in pure LaTeX [neuralatex.com]
7. The Matrix Calculus You Need For Deep Learning [explained.ai]

• Links between climate change and suicidal behavior risks (F. Vergunst, M. Orri, A. Forte, M.-C. Geoffroy)
• Habitual use of GPS negatively impacts spatial memory during self-guided navigation (L. Dahmani, V. D. Bohbot)
• Global gridded population datasets systematically underrepresent rural population (J. Láng-Ritter, M. Keskinen, H. Tenkanen)
• Quirks of cognition explain why we dramatically overestimate the size of minority groups (B. Guay, T. Marghetis, C. Wong, D. Landy)
• Synergistic Signatures of Group Mechanisms in Higher-Order Systems (T. Robiglio, M. Neri, D. Coppes, C. Agostinelli, F. Battiston, M. Lucas, G. Petri)
• Urban sensing using existing fiber-optic networks (J. Liu, H. Li, H. Y. Noh, P. Santi, B. Biondi, C. Ratti)
• High Reconstructability of Degree-Heterogeneous Networks (J.-J. Qin, G. Yan)

You Don’t Know Git

April 2, 2025

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