Can you explain the concept of Semi-Supervised Learning and how it bridges the gap between supervised and unsupervised learning?
- Combines labeled & unlabeled data
- Uses only labeled data
- Uses only unlabeled data
- Uses rewards and penalties
Semi-Supervised Learning bridges the gap by combining both labeled and unlabeled data, utilizing strengths of both supervised and unsupervised.
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