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  1. from keras.models import Sequential
  2. from keras.layers import Dense, Activation
  3. def gradient_descent(X, y, learning_rate=0.01, num_iterations=100):
  4.     m = len(y)
  5.     theta = np.zeros(X.shape[1])
  6.  
  7.     for iteration in range(num_iterations):
  8.         gradients = 2/m * X.T.dot(X.dot(theta) - y)
  9.         theta = theta - learning_rate * gradients
  10.  
  11.     return theta
  12.  
Success #stdin #stdout 2.62s 308956KB
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https://ideone.com/tK7aQN
language:
Python 3 (python  3.9.5)
created:
13 days ago
visibility:
public

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