Activation functions play a crucial role in neural networks, performing a vital function in hidden layers to solve complex problems and to analyze and transmit data throughout deep learning algorithms. There are dozens of activation functions, including binary, linear, and numerous non-linear variants. The activation function defines the output of a node based on a set of specific inputs in machine learning, deep neural networks, and artificial neural networks.