6.2

import random as rnd
import math
import numpy as np
import matplotlib.pyplot as plt

def difL(w):
    return(16*pow(w,3) + 9*pow(w,2) - 12*w)

def Lfun(w):
    return(4*w**4 + 3*w**3 - 6*w**2 - 3)

w = []
maxiter = 150
prec = 0.001
learning_rate = 0.01

w.append(rnd.random()*3)
w.append(w[0] - step * difL(w[0]))
i = 1
error = 0.01

while(error>prec and i<maxiter):
    w.append(w[i] - ( learning_rate * difL(w[i]) ))
    error = np.absolute(w[i]-w[i-1])
    i+=1
    print(error, w[i])

print(Lfun(w[i]))