Since 2020, aggregated from related topics
Unsupervised learning is a type of machine learning where the model learns patterns and relationships from unlabelled data without any guidance from a human. In this approach, the algorithm is required to find structure in the data on its own, such as clusters or patterns, without being provided with explicit labels or targets. Unsupervised learning is commonly used for tasks such as clustering, anomaly detection, and dimensionality reduction. It is a powerful tool for uncovering hidden patterns and insights in data without the need for human supervision.