Supervised / unsupervised learning

Supervised and unsupervised learning are two fundamental approaches to machine learning: in supervised learning, the model learns from data that has been pre-labeled with correct answers, while in unsupervised learning the model searches for hidden patterns, clusters, and relationships in the data without any predefined labels. The choice of approach depends primarily on what data the organization has available and whether it has labeled samples.