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Workflow
ML Pipeline
Order the stages of a machine learning project — from collecting data to monitoring in production.
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Your task
Easy · 1× ptsOrder the basic ML workflow from start to finish
How to play: Tap the steps in the correct order, from first to last.
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What this means
Building an ML model is a pipeline: collect data, clean it, train a model, evaluate it, and deploy. Skip a step or get the order wrong, and the whole thing breaks. This is what ML engineers do every day — and why "just train a model" is never as simple as it sounds.
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