Deep Belief Networks (DBNs), introduced in 2006 by Geoffrey Hinton and colleagues, revolutionised unsupervised learning by enabling hierarchical feature extraction and robust data representation. Widely used in industries like healthcare, finance, and transport, DBNs enhance tasks such as image recognition, NLP, and time-series prediction.
