An activation function decides whether a neuron should "fire" or stay quiet — it's what lets neural networks learn complex, curvy patterns instead of just straight lines.
Imagine it like this: Think of a light switch with a dimmer — not just fully "on" or "off." An activation function decides how strongly a neuron reacts, based on how strong the incoming signal is.
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