What is Data Labeling?

Learning patterns from unlabeled data without explicit target outputs.

Systematic unfairness in model outputs caused by skewed data, assumptions, or modeling choices.

Converting raw data into informative features that a model can use.

A model that can process or generate multiple data types such as text, image, and audio.

Learning representations from unlabeled data by predicting masked or transformed parts.

Training a model with labeled examples that map inputs to known outputs.