Any Deep neural network will consist of three types of layers:
- Input Layer: This layer receives all the inputs and forwards them to the hidden layer for analysis
- Hidden Layer: In this layer, various computations are carried out and the result is transferred to the output layer. There can be n number of hidden layers, depending on the problem you’re trying to solve.
- Output Layer: This layer is responsible for transferring information from the neural network to the outside world.
