An activating function, or activation function, is a mathematical function used in artificial neural networks to introduce non-linearity into the model. This is crucial because it allows the network to learn complex patterns in data. Without non-linear activation functions, a neural network would effectively behave like a linear model, regardless of how many layers it had.
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