The sigmoid activation function is also called the logistic function. It is traditionally a trendy activation function for neural networks. The input data to the function is transformed into a value between 0.0 and 1.0. Input values that are much larger than 1.0 are transformed to the value 1.0. Similarly, values that are much smaller than 0.0 are transformed into 0.0. The shape of the function for all possible inputs is an S-shape from zero up through 0.5 to 1.0. It was the default activation used on neural networks, in the early 1990s.
