What is the key difference between supervised and unsupervised learning?
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ASupervised learning requires human intervention during model training, while unsupervised learning is fully automated
BSupervised learning requires labeled training data, while unsupervised learning works with unlabeled data
CSupervised learning is computationally less expensive than unsupervised learning
DSupervised learning is used for clustering, while unsupervised learning is used for classification
✓ Correct answer: B. Supervised learning requires labeled training data, while unsupervised learning works with unlabeled dataThe fundamental difference between supervised and unsupervised learning is that supervised learning requires labeled training data (with input-output pairs), while unsupervised learning works with unlabeled data and aims to discover patterns or structures within the data without explicit guidance.
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