Unsupervised Learning

Unsupervised learning is a type of machine learning where the algorithm learns patterns from unlabeled data. Unlike supervised learning, there are no pre-defined correct answers or target variables provided to guide the learning process. Instead, the algorithm explores the data to discover hidden structures, relationships, and groupings on its own. Common tasks in unsupervised learning include clustering, dimensionality reduction, and anomaly detection.