Architectures

Deep Neural Networks
It is a neural network that incorporates the complexity of a certain level, which means several numbers of hidden layers are encompassed in between the input and output layers. They are highly proficient on model and process non-linear associations.
Deep Belief Networks
A deep belief network is a class of Deep Neural Network that comprises of multi-layer belief networks.
Steps to perform DBN:
1. With the help of the Contrastive Divergence algorithm, a layer of features is learned from perceptible units.
2. Next, the formerly trained features are treated as visible units, which perform learning of features.
3. Lastly, when the learning of the final hidden layer is accomplished, then the whole DBN is trained.
Recurrent Neural Networks
It permits parallel as well as sequential computation, and it is exactly similar to that of the human brain (large feedback network of connected neurons). Since they are capable enough to reminisce all of the imperative things related to the input they have received, so they are more precise.

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