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AI Glossary
Semi-Supervised Learning
Semi-supervised learning combines a small amount of labeled data with a larger amount of unlabeled data to improve model performance.
Overview
Semi-supervised learning bridges the gap between supervised and unsupervised learning.
It uses a limited set of labeled examples alongside a larger collection of unlabeled data, helping models learn more effectively.
Why It Matters
Labeling data is often expensive and time-consuming. Semi-supervised learning reduces this burden while still producing strong results.
Real-World Example
Image recognition systems trained with a small number of labeled images and millions of unlabeled images.
Related Concepts
- Machine Learning
- Supervised Learning
- Unsupervised Learning
- Deep Learning
- Training Data