```
import numpy as np
def sigmoid(x):
return 1.0/(1+ np.exp(-x))
def sigmoid_derivative(x):
return x * (1.0 - x)
class NeuralNetwork:
def __init__(self, x, y):
self.input = x
self.weights1 = np.random.rand(self.input.shape[1],4)
self.weights2 = np.random.rand(4,1)
self.y = y
self.output = np.zeros(self.y.shape)
def feedforward(self):
self.layer1 = sigmoid(np.dot(self.input, self.weights1))
self.output = sigmoid(np.dot(self.layer1, self.weights2))
def backprop(self):
# application of the chain rule to find derivative of the loss function with respect to weights2 and weights1
d_weights2 = np.dot(self.layer1.T, (2*(self.y - self.output) * sigmoid_derivative(self.output)))
d_weights1 = np.dot(self.input.T, (np.dot(2*(self.y - self.output) * sigmoid_derivative(self.output), self.weights2.T) * sigmoid_derivative(self.layer1)))
# update the weights with the derivative (slope) of the loss function
self.weights1 += d_weights1
self.weights2 += d_weights2
if __name__ == "__main__":
X = np.array([[0,0,1],
[0,1,1],
[1,0,1],
[1,1,1]])
y = np.array([[0],[1],[1],[0]])
nn = NeuralNetwork(X,y)
for i in range(1500):
nn.feedforward()
nn.backprop()
print(nn.output)
```

When importing numpy I got some error, but I fixed it by installing numpy via stash. But if sou try to execute this code in pythonista, you will get heaps of errors. For example, numpy.array() apparently doesn’t exist. Does anyone know why this is the case?

]]>@omz ok, no problem. I just reinstalled Pythonista on my iPad. Obviously it functions now, thanks a lot. I’m sure you hear this frequently, but Pythonista is a great app. I’m just 16yrs old, so it helped a lot at learning coding in general.

Hopefully I didn’t agree that I’m over 18 when signing up this forum :D

]]>