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huggingface/datasets Is the Boring Infrastructure You Actually Need for ML

If you're doing any serious ML work in Python, you're probably already using this library whether you know it or not. Here's an honest look at whether it's worth deliberately adopting versus just tolerating as a transitive dependency.
21,383 stars huggingface/datasets 8 min read

MLflow in 2026: Still the Most Practical MLOps Platform, Now Going All-In on LLMs

MLflow has been the default experiment tracking tool for ML teams for years, and it's now making a serious push into LLM observability, agent evaluation, and prompt management. Here's an honest look at whether it delivers on that expanded scope.
25,260 stars mlflow/mlflow 8 min read

Ray Is the Distributed Python Runtime You Probably Need (But Should Approach Carefully)

Ray is a mature, actively developed distributed compute framework that can genuinely scale Python and ML workloads from a laptop to a cluster. But with 3,500+ open issues and a sprawling surface area, adopting it requires knowing exactly which parts you need.
42,029 stars ray-project/ray 8 min read