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Labels vs No Labels
From: What is Supervised Learning?•View in lesson →
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Supervised learning needs labeled examples—data with "answers" attached. But what if you don't have labels? This simulator shows you how labeled and unlabeled data lead to fundamentally different learning approaches.
🔍 Without Labels
Model sees patterns (gray circles show natural groupings) but has NO GOAL. It can cluster, but doesn't know what's "right" or "wrong".
Behavior: Groups similar things together, but can't predict labels.
Try all four modes to unlock the insight →
Experiment as much as you like; there is no progress to lose.