APPLICATION OF SUPERVISED LEARNING
NEURAL NETWORK
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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A dense multi layer perceptron layer has 300 input values and 200 output values. Assuming no bias, how many parameters does the layer contain?
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500
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6000
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60000
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3000
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Explanation:
Detailed explanation-1: -There are a few different ways to calculate the number of parameters in an MLP neural network, but the most common method is to use the formula: (number of input units + number of hidden units + number of output units) x (number of hidden units + 1).
Detailed explanation-2: -Number of parameters in an MLP network So, 20 weights and 5 bias terms (20+5=25) are trainable parameters between these two layers. In a similar way, we can compute the number of trainable parameters between hidden layer-1 and hidden layer-2 and also between hidden layer-2 and the output layer.
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