Validate Before You Train: The One Habit That Stops AI From Learning the Wrong Thing
Most ML teams have a checklist for deploying a model. Fewer have one for the data that goes into it. That gap is where data poisoning, silent bias, and months of "why is accuracy drifting" debugging a
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