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An Auto-Encoder is a type of neural network that learns to reconstruct its input by encoding it into a lower-dimensional representation and then decoding it back to the original space. Autoencoders are used for unsupervised learning tasks, such as feature learning and dimensionality reduction, and can be modified to create variational autoencoders or generative adversarial networks (GANs).
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