COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Which of these is not one of the three layers used in machine learning models?
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input
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hidden
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output
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activation, hidden, and output
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Explanation:
Detailed explanation-1: -The neural network consists of three layers: an input layer, i; a hidden layer, j; and an output layer, k.
Detailed explanation-2: -There are three layers; an input layer, hidden layers, and an output layer. Inputs are inserted into the input layer, and each node provides an output value via an activation function. The outputs of the input layer are used as inputs to the next hidden layer.
Detailed explanation-3: -A layer is the highest-level building block in deep learning. A layer is a container that usually receives weighted input, transforms it with a set of mostly non-linear functions and then passes these values as output to the next layer.
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