Answer:
The answer is many top commercial ANNs forgo hidden layers completely.
Explanation:
Hidden layers are artificial neural networks which her directly hidden in between input layers and output layers. It increase the required computation exponentially, improves prediction capabilities and they are not visible as a network output. It ensures there it calculates the weighted inputs and net inputs to produce the actual output. The more the number of hidden layers in a neural network, the longer it takes for it to produce the output and it will enable the neural network to solve more complex problems.
