Representation Learning for Unstructured Data

This field focuses on automatically discovering meaningful data representations (embeddings) from raw, unstructured data like text, images, or audio, without explicit human labeling. These learned representations capture semantic and syntactic information, making the data more amenable to downstream machine learning tasks. Techniques involve deep neural networks and self-supervision.