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Yes, it’s 2026 — and we’re already focused on an eventful 12 months of growth and learning here at TDS. We’ve also published many stellar articles last month, including at the peak of the vacation season, and we wouldn’t want you to miss out on any of them.
This week, we’re devoting the Variable to at least one last 2025 hurrah, highlighting a few of our hottest stories from December. Make no mistake, nonetheless: they cover timely and actionable topics in machine learning, data science, and AI, and can remain relevant for weeks and months to return.
GraphRAG in Practice: The right way to Construct Cost-Efficient, High-Recall Retrieval Systems
When “vanilla” RAG systems now not cut it, chances are you’ll need to explore the ability of GraphRAG — and Partha Sarkar‘s detailed guide is an excellent start line for anyone all in favour of tinkering with this powerful approach, which leverages hybrid pipelines and may result in lower costs.
Six Lessons Learned Constructing RAG Systems in Production
For extra hands-on RAG insights, we highly recommend Sabrine Bendimerad’s roundup of best practices, covering data quality, evaluation, and more.
The right way to Use Easy Data Contracts in Python for Data Scientists
Quick and focused, Eirik Berge presents a guide to using open-source library Pandera if you aim to define schemas as class objects.
Other December Highlights
From learning algorithms with Excel to improving Pandas’ performance, listed here are just a few more of last month’s most-read and -shared stories.
The Machine Learning and Deep Learning “Advent Calendar” Series: The Blueprint, by Angela Shi
How Agent Handoffs Work in Multi-Agent Systems, by Kenneth Leung
Reading Research Papers within the Age of LLMs, by Parul Pandey
7 Pandas Performance Tricks Every Data Scientist Should Know, by Benjamin Nweke
What Happens When You Construct an LLM Using Only 1s and 0s, by Moulik Gupta
Meet Our Latest Authors
We hope you’re taking the time to explore excellent work from TDS contributors who recently joined our community:
- Jasper Schroeder shared helpful takeaways from the Advent of Code programming challenge he recently accomplished.
- Morris Stallmann (with coauthor Sebastian Humberg) offered a comprehensive, pragmatic primer on data drift (and detect it in a timely manner).
- Alon Lanyado focused on a special challenge data scientists and ML practitioners often face: covariance shift.
Do your Latest 12 months’s resolutions include publishing on TDS and joining our Writer Payment Program? Now’s the time to send along your latest draft!
