gs gs126 Neural Networks - Gradient Checking - Quiz No.1
gs gs126 Neural Networks Quiz
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Question 1: What do you mean by gradient checking?
It is a test that makes sure that the execution of backpropagation is bug free
It is a test which can be referred as external software testing
It is a behaviour testing of a software
It is a type of software testing in which the system is tested against the functional requirements and specification
Question 2: What is the purpose of gradient checking?
To train the network in incorrect direction and to increase the accuracy of the output
To train the network function normally and to increase its accuracy of the output
To train the network in such a way that the prediction is same with or without error
To train the network in such a way that it works normally for some cases and abnormally for some cases
Question 3: Which of the following statement is incorrect about backpropagation?
It is an algorithm commonly used to train the neural networks
It helps to adjust the weights of the neurons so that the accuracy of the output increases
It is a method of training the neural networks to perform tasks more accurately
The idea behind backpropagation is not to test how wrong the neural network is
Question 5: Which of the following statement is not true about gradient checking?
It is used during the training of the neural network
It doesn’t work with dropout
It is used for only debugging purpose
Runs at random initialization
Question 6: Why should one stop gradient checking once it is done before running the network for entire set of training iterations?
Because it would increase the speed of training process
Because it would change the output of the training process
Because it would slow down the speed of training process
Because it would nullify the output
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