![]() ![]() If the sigmoid's output is a variable "out", then the derivative is simply out * (1-out). One of the desirable properties of a sigmoid function is that its output can be used to create its derivative. Notice that this function can also generate the derivative of a sigmoid (when deriv=True). ![]() It also has several other desirable properties for training neural networks. We use it to convert numbers to probabilities. A sigmoid function maps any value to a value between 0 and 1. While it can be several kinds of functions, this nonlinearity maps a function called a "sigmoid". This imports numpy, which is a linear algebra library. That's kinda what I did while I wrote it. Opencanvas 1.1 networking tutorial code#Recommendation: open this blog in two screens so you can see the code while you read it. Let's walk through the code line by line. Everything in the network prepares for this operation.
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