Data labeling for AI: quality, cost and model readiness
Data labeling is the work of attaching the correct answer to raw examples (a box around a pedestrian, an intent on a support ticket, a speaker on an audio clip) so a model can learn from them or be tested against them. Whether your model works in production depends more on how consistent those labels
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