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A convolutional neural network (cnn) is a neural network where one or more of the layers employs a convolution as the function applied to the output of the previous layer. Typically for a cnn architecture, in a single filter as described by your number_of_filters parameter, there is one 2d kernel per input channel A cnn will learn to recognize patterns across space while rnn is useful for solving temporal data problems
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