Unsupervised Learning
Unsupervised learning finds structure in unlabeled data — clustering, density estimation, dimensionality reduction — without explicit target labels.
Classical unsupervised methods differ from self-supervised LM pretraining, which creates pretext labels from the data itself (e.g., next token).