These networks have the same number of output and input neurons. By having a hidden layer smaller than the input layer, the encoder forces the input data to be represented in a compressed version. Later, the decoder reconstructs the data only using compressed hidden layer outputs. Auto encoders specialize in unsupervised learning- unlabelled data without input output pairs. Auto encoders are mainly used to reduce the dimensionality of data.
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