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In [2]:

    
import numpy as np

def sigmoid(x):
    # TODO: Implement sigmoid function
    return 1 / (1 + np.exp(-x))



In [3]:

    
inputs = np.array([0.7, -0.3])
weights = np.array([0.1, 0.8])
bias = -0.1



In [4]:

    
# TODO: Calculate the output
output = sigmoid(np.matmul(inputs, weights) + bias)

print('Output:')
print(output)









    



Output:
0.432907095035



In [ ]: