{"version":"1.0","type":"rich","provider_name":"gaks.ai AI Glossary","provider_url":"https://gaks.ai/glossary","title":"Semi-Supervised Learning — AI Glossary","author_name":"Glenn Katrud Solheim","author_url":"https://gaks.ai","width":600,"height":200,"html":"

AI Glossary — gaks.ai

Semi-Supervised Learning

A training approach that combines a small amount of labeled data with a large amount of unlabeled data. The labeled examples guide the learning signal while the unlabeled data helps the model build richer representations of the underlying structure. Semi-supervised learning is practical in many real-world settings where labeling everything is too costly, and is closely related to self-supervised learning in its motivation if not its mechanics.

Source: gaks.ai/glossary/semi-supervised-learning →
"}