What is semi-supervised learning? How does it work?

Semi-Supervised Learning is a machine learning approach that uses a small amount of labeled data combined with a large amount of unlabeled data to train models. Unlike supervised learning, which relies entirely on labeled datasets, and unsupervised learning, which uses none, semi-supervised learning sits in the middle.

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