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Softmax annotated

From Algolit

Revision as of 17:50, 25 October 2017 by Hans (talk | contribs)
Type: Algolit extension
Technique(s): mathematics, softmax function, python
Developed by: Algolit

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 regression 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