Implementing Essential Deep Learning Module

In this project, I am trying to implement some deep learning modules which are used for classification. I am trying to implement some important modules like Radial Basis Kernel SVM, Radial Basis Function Network and Deep belief Nets.
Deep belief nets:- They are probabilistic generative models that are composed of multiple layers of stochastic, latent variables. The latent variables typically have binary values and are often called hidden units or feature detectors.

Radial Basis Function Network:- It is an artificial neural network that uses radial basis functions as activation functions. The output of the network is a linear combination of radial basis functions of the inputs and neuron parameters.

Radial Basis Function Kernel:- It is also called the RBF kernel, or gaussian kernel, is a kernel that is in the form of a radial basis function (more specifically, a Gaussian function).

We can use these deep learning classification modules for various purposes like speech recognition, handwriting recognition, biometric identification, document classification etc.