👉 Sigmoidopexy is a type of neural network architecture that was proposed by Andrew Ng and Jian Sun in their book "Machine Learning for Computer Vision" (2015). It is based on the concept of an activation function, which can be thought of as a "sigmoid" function. In this context, the term "sigmoidopexy" refers to the sigmoid activation function applied to the output of the network. The sigmoid opexy architecture is particularly useful for tasks that
