The sigmoid (shown in Fig. 7 .1) has a number of advantages; it maps the output into the range [0, 1], which is useful in squashing outliers toward 0 or 1. And it's differentiable, which as we saw in Section 5.8 will be handy for learning. Substituting Eq. 7.2 into Eq. 7.3 gives us the output of a neural unit: