Ans: Deep Autoencoders consist of two identical deep belief networks. One network for encoding and another for decoding. Typically, deep autoencoders have 4 to 5 layers for encoding and the next 4 to 5 layers for decoding. We use unsupervised layer by layer pre-training. The layers are restricted Boltzmann machines, which are the building blocks of deep-belief networks.
Explain about Deep autoencoders?
