How Many Types of deep learning Networks are there?
First, understand what is deep learning network? Deep learning networks are mathematical models that are used to imitate the human brain as it is to solve problems using unstructured data, these mathematical models are built in the form of neural networks that contain neurons. Neural networks are divided into three major layers which are the input layer (the first layer of the neural network), the hidden layer (all the middle layers of the neural network), and the output layer (the last layer of the neural network). Based on this type of data we will deal with these neural networks which are classified as feed-forward neural networks, CNNs, RNNs, modular neural networks, etc. Now let us know how many types of deep learning networks are over there? No.1 radial basis function neural network: Such neural networks typically have more than 1 layer, preferably two layers. In such a network, the relative distance from any point to the center is calculated and passed on to the next layer. Radi...