In a neural network, numeric data points, called 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.
The activation function is a mathematical “gate” in between the
input feeding the current neuron and its output going to the next
layer. It can be as simple as a step function that turns the neuron
output on and off, depending on a rule or threshold. Or it can be a
transformation that maps the input signals into output signals that
are needed for the neural network to function