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and speech synthesis. 5. Autoencoders Autoencoders are unsupervised learning models that aim to learn efficient representations of input data. Consisting of an encoder and a decoder, they are widely used in dimensionality reduction, anomaly detection, and image denoising. Variational Autoencoders