Question

What are the steps for using a gradient descent algorithm? 1. Calculate error between the actual value and the predicted value 2. Repeat until you find the best weights of network 3. Pass an input through the network and get values from output layer 4. Initialize random values for weight and bias 5. Go to each neurons which contributes to the error and change its respective values to reduce the error A) 4,3,1,5,2 B) 1,2,3,4,5 C) 3,4,5,2,1 D) 2,3,4,5,1

Answer 1

Answer:

   A) 4,3,1,5,2

Explanation:

1. Initialize random values for weight and bias
2. Pass an input through the network and get values from the output layer
3. Calculate the error between the actual value and the predicted value
4. Go to each neuron that contributes to the error and change its respective values to reduce the error
5. Repeat until you find the best weights of the network

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