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Why I Moved from Jupyter Notebooks to End-to-End ML Pipelines
Notebooks are great. They're also a trap.
Notebooks are wonderful for exploration. They are a disaster for deployment. This post is about the moment that distinction stopped being theoretical for me, and what I changed in my workflow as a result…
The hidden cost of “it runs in my notebook”
State that lives only in cell outputs. Cell-execution order that nobody else can reproduce. Imports six layers deep that nobody documents…
What replaces them
A small, opinionated stack: a feature pipeline, a training script, a model registry, and a serving layer. Boring. Reliable. Reviewable.