Which statement correctly distinguishes supervised from unsupervised learning?
A.Supervised = data without labels; unsupervised = labeled data
Exactly backwards.
B.Supervised = trained on labeled data (regression/classification); unsupervised = finds structure in unlabeled data (clustering)
Correct definition.
C.Supervised requires GPUs; unsupervised runs on CPUs
Hardware has nothing to do with the supervised/unsupervised distinction.
D.They differ only in dataset size
The difference is labeling, not volume.
Why this answer
Supervised = historical examples with known answers (labels) → predict labels for new data (regression, classification). Unsupervised = unlabeled data → discover structure (clustering, dimensionality reduction). Reinforcement learning (reward-based) is the third family.
Correct answer: B · Last reviewed 2026-02-14
Official AWS references
Practice this interactively
Answer without seeing the solution first in the Machine Learning Principles practice session.
Practice Machine Learning Principles