An autoencoder is a type of unsupervised neural network that learns to represent input data in a compressed latent space. This compressed representation captures the essential features of the data ...
What’s the Latent Space ? An Autoencoder is made of two components: an Encoder & a Decoder. The Encoder brings the input data from a high dimensional representation to a bottleneck layer, where the ...
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