neural-network-tutorial

Simple neural network implementation in python

Test Results

And Function
Inputs:[0, 0] Target:[0] Result:[0.0]
Inputs:[0, 1] Target:[0] Result:[-0.0]
Inputs:[1, 1] Target:[1] Result:[0.99]
Inputs:[1, 0] Target:[0] Result:[0.0]
Mean Square Error = 2.806539502841615e-05

Or Function
Inputs:[0, 0] Target:[0] Result:[0.0]
Inputs:[0, 1] Target:[1] Result:[1.0]
Inputs:[1, 0] Target:[1] Result:[1.0]
Inputs:[1, 1] Target:[1] Result:[1.0]
Mean Square Error = 5.746578530894208e-06

Xor Function
Inputs:[0, 0] Target:[0] Result:[0.0]
Inputs:[0, 1] Target:[1] Result:[0.99]
Inputs:[1, 0] Target:[1] Result:[0.99]
Inputs:[1, 1] Target:[0] Result:[0.0]
Mean Square Error = 0.00026675172503416554

Nand Function
Inputs:[0, 0] Target:[1] Result:[1.0]
Inputs:[0, 1] Target:[1] Result:[1.0]
Inputs:[1, 0] Target:[1] Result:[1.0]
Inputs:[1, 1] Target:[0] Result:[-0.0]
Mean Square Error = 8.442442478476193e-06

Nor Function
Inputs:[0, 0] Target:[1] Result:[0.99]
Inputs:[0, 1] Target:[0] Result:[0.0]
Inputs:[1, 0] Target:[0] Result:[0.0]
Inputs:[1, 1] Target:[0] Result:[-0.0]
Mean Square Error = 8.37314056446251e-06

Xnor Function
Inputs:[0, 0] Target:[1] Result:[0.99]
Inputs:[0, 1] Target:[0] Result:[0.0]
Inputs:[1, 0] Target:[0] Result:[0.0]
Inputs:[1, 1] Target:[1] Result:[0.99]
Mean Square Error = 0.00036547859452619236