Deep Learning Architectures

There are several types of Deep learning architectures, also known as artificial neural networks of multiple nonlinear layers. Characteristics of input data and the objective of the research work helps one and individual to decide which Deep Learning architecture is to be used and when. Deep Neural Network DNN: -Various Deep Learning Architectures in DNN are designed on the basis of building blocks of Neural Networks. These building blocks are based on Multilayer Perceptron (MLP) which uses Perceptron's, Stacked Auto-Encoder (SAE) which uses Auto-Encoders, and Deep Belief Networks (DBNs) which use Restricted Boltzmann machines (RBMs). Convolution Neural Network CNN: CNN's architectures are consist of different layers like convolution layers, nonlinear layers, and pooling layers.