Activation Function : A Comprehensive Guide | Learn CPlusPlus
An activation function is a mathematical operation used in neural networks to determine the output of a node based on its input. It introduces non-linearity into the model, enabling it to learn complex patterns. Common types include Sigmoid, ReLU, and Tanh. By influencing how signals are propagated through the network, activation functions play a crucial role in training deep learning models. To learn more about it, please visit the Learn CPlusPlus blog post.
