|Technique(s):||mathematics, softmax function, python|
Softmax annotated is a annotated script of a softmax function written in python. The basis of the code is found at the Softmax function page on the English Wikipedia. This script was part of proces to get a better understanding of the mathematics behind neural networks.
The softmax function provides a very basic classifier based on logistic regression. It is a building block used in neural networks. A neural network can be seen as running multiple logistic regressions in parallel, which then feed into another layer of (multiple) logistic regressions and so on.
More information see Lecture 4 of the Stanford Deep Learning course