Unverified50% confidenceFactExact time
A typical ML workflow can be abstracted into five steps: data, model training, model evaluation, deployment, and monitoring, and in actual operation it often forms a continuously looping closed loop, where monitoring problems force adjustments to data strategy and model retraining.
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10/12/2026
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