def train(rounds):
    weight_one = 0.5
    weight_two = 0.8
    for i in range(rounds):
        input_one = r.randint(0,1)
        input_two = r.randint(0,1)
        if input_one == 0 and input_two == 0:
            wish_output = 0
        else:
            wish_output = 1
        learning_rate = 0.1
        output = input_one * weight_one + input_two * weight_two
        print(i,' X1: ', input_one, ' X2: ', input_two, ' output = ', output)
        error = wish_output - output
        delta_weight_one = learning_rate * error * input_one
        delta_weight_two = learning_rate * error * input_two
        weight_one = weight_one + delta_weight_one
        weight_two = weight_two + delta_weight_two

train(99999999)

import random

LR = 0.1
OR_GATE = {(0,0): 0, (0,1): 1, (1,0): 1, (1,1): 1}

def train(rounds):
    b = random.random()
    w1 = random.random()
    w2 = random.random()
    for i in range(rounds):
        input_one = random.randint(0,1)
        input_two = random.randint(0,1)
        wish_output = OR_GATE[(input_one, input_two)]

        output = b + input_one * w1 + input_two * w2
        error = wish_output - output
        
        delta_b = LR * error
        delta_w1 = LR * error * input_one
        delta_w2 = LR * error * input_two
        
        b = b + delta_b
        w1 = w1 + delta_w1
        w2 = w2 + delta_w2
        
    for x1, x2 in [(0,0), (0,1), (1,0), (1,1)]:
        print(x1, x2, b + x1*w1 + x2*w2)

train(100000)

Output:
0 0 0.18145152675687892
0 1 0.7848461458328603
1 0 0.6773077637591502
1 1 1.2807023828351316