APPLICATION OF SUPERVISED LEARNING
DEEP LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Backpropagation works by first calculating the gradient of ____ and then propagating it backwards.
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Sum of squared error with respect to inputs
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Sum of squared error with respect to weights
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Sum of squared error with respect to outputs
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None of the above
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Explanation:
Detailed explanation-1: -Choosing Input and Output: The backpropagation algorithm’s first step is to choose a process input and set the desired output.
Detailed explanation-2: -Backpropagation is a process involved in training a neural network. It involves taking the error rate of a forward propagation and feeding this loss backward through the neural network layers to fine-tune the weights. Backpropagation is the essence of neural net training.
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