Is it necessary to use Activation functions in neural networks?

src: V7 labs

Yes, activation functions are necessary in neural networks. In fact, without activation functions, a neural network would just be a linear model, regardless of the number of layers it has.

The purpose of activation functions is to introduce nonlinearity into the network. Nonlinearity allows the neural network to learn complex patterns and relationships