Supervised Learning

A subfield of AI where models learn patterns from data to make predictions or decisions, improving with experience ra...

A structured collection of examples used to train/evaluate models; quality, bias, and coverage often dominate outcomes.

Learning structure from unlabeled data, such as discovering groups, compressing representations, or modeling data dis...

Training with a small labeled dataset plus a larger unlabeled dataset, leveraging assumptions like smoothness/cluster...

Learning from data by constructing “pseudo-labels” (e.g., next-token prediction, masked modeling) without manual ...

Learning where data arrives sequentially and the model updates continuously, often under changing distributions.

A subfield of AI where models learn patterns from data to make predictions or decisions, improving with experience ra...