The vanilla gradient descent formula updates the parameters as:
new weights = old weights - learning_rate * gradient

In the linked tutorial the same formula is used as far as I can see:

To decrease the error, we then subtract this value from the current weight (optionally multiplied by some learning rate, eta, which we’ll set to 0.5):