What is Data Labeling?
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The process of annotating raw data with informative tags to create training datasets for supervised machine learning.
Data labeling involves human annotators or automated tools tagging text, images, or audio with categories, bounding boxes, or other labels. Label quality directly determines model accuracy, making it one of the most important and expensive parts of the ML pipeline.