APPLICATION OF SUPERVISED LEARNING
NEURAL NETWORK
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Divide the picture in to pixels
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Assign a pixel in each neuron in the input layer
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Do calculations to find the values in the hidden layers
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Predict the output
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Find the error
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Detailed explanation-1: -PixelRNN is a deep neural network that sequentially predicts the pixels in an image along two spatial dimensions. Pixels have discrete values from multinomial distribution implemented with softmax layer. Each pixel is determined by three values: R, G, B.
Detailed explanation-2: -Input Layer– First is the input layer. This layer will accept the data and pass it to the rest of the network. Hidden Layer– The second type of layer is called the hidden layer. Hidden layers are either one or more in number for a neural network.
Detailed explanation-3: -Information is fed into the input layer which transfers it to the hidden layer. The interconnections between the two layers assign weights to each input randomly. A bias added to every input after weights are multiplied with them individually. The weighted sum is transferred to the activation function. More items •22-Sept-2022