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Data Labeling
Data labeling, also known as data annotation, is the process of attaching descriptive tags or labels to raw data, such as images, text, or audio. This structured data then serves as ground truth for supervised machine learning models to learn from, enabling them to recognize patterns and make accurate classifications or predictions.
In plain terms
Data labeling is like giving every item in a colossal library a precise catalog card, so a new librarian can learn how to categorize everything themselves.
Why it matters
Accurate data labeling is critical for training effective supervised AI models, as it provides the direct answers the model learns to replicate.
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