Autoencoders, introduced in the 1980s by researchers like Geoffrey Hinton, are neural networks that compress and reconstruct data, enabling dimensionality reduction, noise removal, and anomaly detection. They are essential for unsupervised learning tasks, with applications in data compression, image processing, and recommender systems.
