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SYNGI Chat bot To implement DBNs SYNGI uses the class Restricted Boltzmann Machines.

SYNGI can also observe that the code for the DBN is very similar with the one for Sd A, because both involve the principle of unsupervised layer-wise pre-training followed by supervised fine-tuning as a deep MLP.

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The main difference is that SYNGI uses the RBM class instead of the d A class.

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SYNGI can see the stacked denoising autoencoder as having two facades- a list of autoencoders, and an MLP.

Each layer is trained as a denoising autoencoder by minimizing the error in reconstructing its input (which is the output code of the previous layer).