goal = 42 # Label weight = 0.0 input_val = 0.5 iteration = 0

for iteration in range(15): # The output of the algorithm output = input_val * weight # Calculate the error. Negative errors would hinder the learning process, so errors are squared to ensure that the error metric is positiv error = (output - goal) ** 2 # Calculate the difference between the output and the goal value delta = output - goal # Calculate weight delta, the value with wich we alter the weight weight_delta = input_val * delta # Adjust the weight weight = weight - weight_delta # Update the iteration number iteration = iteration + 1 # Print out the results of the iteration print('----- Iteration {} -----'.format(iteration)) print('Error: {}'.format(error), 'Output: {}'.format(output))