Which of the following options represents the correct sequence of steps involved in employing a gradient descent algorithm?
1. Calculate the difference between the actual and predicted values.
2. Repeat until you've found the best network weights.
3. Get values from the output layer by passing an input across the network.
4. Create a random weight and bias.
5. To lessen the error, go to each neuron that contributes to the error and modify its value.
4, 3, 1, 5, 2
1, 2, 3, 4, 5
3, 2, 1, 5, 4
5, 4, 3, 2, 1
