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A Neural Network in 11 lines of Python
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| X = np.array([ [0,0,1],[0,1,1],[1,0,1],[1,1,1] ]) | |
| y = np.array([[0,1,1,0]]).T | |
| syn0 = 2*np.random.random((3,4)) - 1 | |
| syn1 = 2*np.random.random((4,1)) - 1 | |
| for j in xrange(60000): | |
| l1 = 1/(1+np.exp(-(np.dot(X,syn0)))) | |
| l2 = 1/(1+np.exp(-(np.dot(l1,syn1)))) | |
| l2_delta = (y - l2)*(l2*(1-l2)) | |
| l1_delta = l2_delta.dot(syn1.T) * (l1 * (1-l1)) | |
| syn1 += l1.T.dot(l2_delta) | |
| syn0 += X.T.dot(l1_delta) | |
| ## |
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