Labeled vs Unlabeled Data

The key distinction between supervised and unsupervised learning lies in whether the training data includes target labels. Labeled data pairs each input with its correct output, while unlabeled data contains only the inputs themselves.

Labeling data is expensive and time-consuming — understanding which paradigm fits your problem determines whether you need that costly annotation effort.