A logistic function is a form of sigmoid functiion often used as a weak {[threshold}} in an neural network. Like a step function it maps unbounded values to a finite [0,1] range and is zero for large negatuve values and one for lareg postuve values. However, unlike a step function the prcess is smooth with a near linear section in the middle and gently asymptotes for more edxtreme values. This is imprtant for machine learning as, in general, it is easier to learn {[contnuous}} features.
Used on Chap. 6: page 115
Logistic function equation and graph