Unsupervised learning

Unsupervised learning is a type of machine learning where computers find patterns and structure in data without being explicitly told what to look for, unlike supervised learning where humans provide labeled examples to guide the process. Imagine sorting a pile of unlabeled photos into groups—the computer would automatically identify similarities like color, shape, or content and organize them into categories on its own. This approach is particularly useful for discovering hidden patterns in large datasets that humans might never notice, making it valuable for tasks like customer segmentation, anomaly detection, and understanding genetic data.