Unsupervised Learning

Training that uses unlabeled data, asking the model to discover structure on its own. Clustering algorithms group similar examples, dimensionality reduction compresses high-dimensional data, and self-supervised methods generate their own training signal from the input. Most of the data on the internet is unlabeled, which makes this category strategically important.

Definición editorial de DecipherU. Para definiciones técnicas autorizadas, consulta NIST AI RMF, ISO/IEC 42001, o las publicaciones oficiales de los laboratorios de IA.