A technique used for reducing the number of input features in a dataset without losing important information. Popular algorithms include Principal Component Analysis (PCA), t-Distributed Stochastic Neighbor Embedding (t-SNE), Linear Discriminant Analysis (LDA), and Factor Analysis.