Unsupervised Learning

Unsupervised learning discovers hidden structures in unlabeled data. Common techniques include clustering (grouping similar items), dimensionality reduction, and anomaly detection. It is used for customer segmentation, topic modeling, and data exploration. Self-supervised learning, which powers LLM pre-training, is a related paradigm.