What Is the Role of Activation Functions in a Neural Network?

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Sundus F Hantoosh

Dear Doctor

"Activation functions are necessary for neural networks because, without them, the output of the model would simply be a linear function of the input."

"Activation functions play an integral role in neural networks by introducing nonlinearity. This nonlinearity allows neural networks to develop complex representations and functions based on the inputs that would not be possible with a simple linear regression model."

Manuel G Forero

Activation functions are fundamental to neural networks as they introduce non-linearity, allowing a network to fit any type of boundary and model complex relationships in the data. Thus, non-linear transformations are crucial for learning intricate patterns, preventing the network from behaving like a linear model.