What sequential steps are involved in employing a gradient descent algorithm?

$1.$ Calculate the error between the actual value and the predicted value

$2.$ Reiterate until you find the best weights of the network

$3.$ Pass an input through the network and get values from the output layer

$4.$ Initialize random weight and bias

$5.$ Go to each neuron that contributes to the error and change its respective values to reduce the error

Question $6$Answer

a$.$

$1,2,3,4,5$

b$.$

$4,3,1,5,2$

c$.$

There are missing steps not listed above

d$.$

$4,2,1,5,3$

e$.$

$5,4,3,2,1$