Unsupervised learning

Unsupervised learning is a type of machine learning where algorithms find patterns, relationships, or structures in raw, unlabeled data. There are no predefined outcomes or target variables. It is used to identify hidden signals in the data that are not obvious at first glance.

Example

In finance, unsupervised learning methods such as clustering can segment customers based on spending habits, account balances, and other behavioral traits. By grouping customers with similar characteristics, financial institutions can adapt products, services, and marketing strategies to fit the needs of each segment more closely.