Unsupervised Learning
Unsupervised learning discovers hidden structure in data through methods such as clustering and representation learning.
Definition
Unsupervised learning is a type of machine learning in which models identify patterns in data without labelled training examples.
How It Works in AI
Instead of learning from predefined answers, unsupervised methods discover hidden structure in data using techniques such as clustering, dimensionality reduction, and representation learning. This lets models group similar items and build internal representations of meaning from raw data.
Unsupervised learning is central to modern AI systems and language model training because massive unlabelled corpora are easier to obtain than fully annotated datasets. It provides the foundation for strong embeddings and broad generalisation.