Core Concepts

Supervised vs. Unsupervised Learning

Supervised learning trains a model on labeled examples, where each input comes with the correct answer, so it learns to predict labels for new inputs. Unsupervised learning works with unlabeled data, finding structure such as clusters or patterns on its own. Many modern systems combine both, along with self-supervised pretraining.