Unsupervised Learning

Fundamentals

Training AI on data without labels, letting it discover structure on its own - groups, patterns, and oddities.

In unsupervised learning nobody provides correct answers. The model gets raw data and finds structure by itself: customers who behave similarly, transactions that look unlike all the others, topics that recur across documents.It is the go-to approach when labeling data is impossible or too expensive. Typical uses are customer segmentation, anomaly and fraud detection, and compressing data down to its essential patterns before further analysis.