Activation functions in Neural Networks

An activation function introduces non-linearity into neural networks, enabling them to learn complex patterns. Without this non-linearity, the network would behave like a linear regression model. Activation functions help neurons make decisions by calculating the weighted sum of inputs and adding a bias. This feature allows backpropagation to update weights and biases effectively. Non-linearity empowers neural networks to solve complex, non-linear problems and learn abstract patterns in data.

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