exemple python gradient
import numpy as np
class Model():
def __call__(self, x):
return 2 * (2 * x ** 2 - 10) * 4 * x
alpha = 0.005
x = 5.0
norme_epsilon= 100
seuil_epsilon = 0.001
ma_fonction = Model()
while norme_epsilon > seuil_epsilon:
dfx_dx = ma_fonction(x)
norme_epsilon = np.abs(dfx_dx)
x = x - alpha * dfx_dx
print(x)