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Problem 1 ( 3 0 Points ) : Build an convolutional neural network,the function should return model with the following specifications: First Convolutional Layer: Uses
Problem Points: Build an convolutional neural network,the function should return model with the following specifications:
First Convolutional Layer: Uses filters with a kernel size of 'relu' activation and pixels, grayscale as input images size.
First Pooling Layer: Uses max pooling with a pool size of and a stride of
Second Convolutional Layer: Uses filters with a kernel size of and 'relu' activation.
Second Pooling Layer: Uses max pooling with the same specifications as the first pooling layer.
Flattening Layer: Converts the feature map to a D array.
First Dense Layer: Has units with 'relu' activation.
Second Dense Layer: Has units with 'relu' activation.
Third Dense Layer: Has units with 'softmax' activation.
The network should be compiled using Adam optimizer, categoricalcrossentropy loss function and accuracy as a metric.
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