Neural Networks

How do activation functions affect neural network learning and performance?

Answer:

Activation functions are fundamental in neural networks because they introduce non-linearity, enabling accurate modelling of complex data patterns. Functions such as ReLU, sigmoid, and softmax support tasks ranging from efficient training to classification and prevent models from behaving as linear alternatives.

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