Answer / Yogesh Pandey

Activation functions are used in artificial neural networks to introduce non-linearity. They transform the output of a neuron (summed weighted input) into a final output signal, which can have a value between -1 and 1 or 0 and 1 depending on the function. The activation function determines the decision boundary for classification problems and the shape of the learned functions in regression problems.

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