Artificial Intelligence, Data Science, Machine Learning, Heartbeat, Gradient Descent.
W) + b # taking the partial derivative of coefficients dW = (2/m) * np.dot(X.T, (y_pred - y)) db = (2/m) * np.sum(y_pred - y) # updates to coefficients W -= alpha * dW b -= alpha * db params["W"] = W params["b"] = b return params Several different adaptations could be made to gradient descent to