Within the domain of unsupervised machine learning is unsupervised clustering, also known as “ clustering analysis,” which enables organizations to group unlabeled data into meaningful categories.

In the world of machine learning, algorithms thrive on unsupervised data. They analyze large volumes of information without explicit labels, and yet still manage to learn useful patterns.

Machine learning can be supervised, unsupervised, or semi-supervised. In supervised learning, models are trained on labeled data, meaning the input data is paired with the correct output.