Unsupervised learning
Unsupervised learning is a machine learning type that looks for data patterns. Unlike supervised learning, unsupervised learning doesn’t learn from labeled data. This type of machine learning is often used to develop predictive models and to create clusters. For example, you can use unsupervised learning to group customers based on purchase behavior, and then make product recommendations based on the purchasing patterns of similar customers. Hidden Markov models, k-means, hierarchical clustering, and Gaussian mixture models are common algorithms used during unsupervised learning.