Commonly used activation functions in deep learning you must know !

Activation functions helps to determine the output of a neural network. These type of functions are attached to each neuron in the network, and determines whether it should be activated or not, based on whether each neuron's input is relevant for the model's prediction. Activation function also helps to normalize the output of each neuron to a range between 1 and 0 or between -1 and 1. In a neural network, inputs are fed into the neurons in the input layer. Each neuron has a weight, and multiplying the input number with the weight gives the output of the neuron, which is transferred to the next layer.