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A neural network in 9 lines of Python code.
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from numpy import exp, array, random, dot | |
training_set_inputs = array([[0, 0, 1], [1, 1, 1], [1, 0, 1], [0, 1, 1]]) | |
training_set_outputs = array([[0, 1, 1, 0]]).T | |
random.seed(1) | |
synaptic_weights = 2 * random.random((3, 1)) - 1 | |
for iteration in xrange(10000): | |
output = 1 / (1 + exp(-(dot(training_set_inputs, synaptic_weights)))) | |
synaptic_weights += dot(training_set_inputs.T, (training_set_outputs - output) * output * (1 - output)) | |
print 1 / (1 + exp(-(dot(array([1, 0, 0]), synaptic_weights)))) |
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Milo Spencer-Harper wrote this article in 2015 on medium.com