What is the role of activation functions in neural networks?
The question is about Neural Networks
Answer:
Activation functions introduce non-linearity to neural networks, enabling them to model complex patterns. Common functions include ReLU (rectified linear unit) for computational efficiency, sigmoid for binary outputs, and softmax for multi-class classification. Without activation functions, networks would behave like linear models, limiting their effectiveness.
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