unsupervised learning

In contrast to supervised learning, in unsupervised learning, data only comes with inputs , but not output labels . Algorithm has to find structure in the data.

• clustering: group similar data points together
• anomaly detection: find unusual data points
• dimensionality reduction, such as PCA: compress data using fewer numbers