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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. A cnn will learn to recognize patterns across space while rnn is useful for solving temporal data problems What will a host on an ethernet network do if it receives a frame with a unicast destination mac address that does not match its own mac address It will discard the frame It will forward the frame to the next host It will remove the frame from the media Cisco ccna v7 exam answers full questions activities from netacad with ccna1 v7.0 (itn), ccna2 v7.0 (srwe), ccna3 v7.02 (ensa) 2024 2025 version 7.02 What three configuration steps must be performed to implement ssh access to a router (choose three.) a password on the console line an ip domain name a user account an enable mode password a unique hostname an encrypted password I think the squared image is more a choice for simplicity There are two types of convolutional neural networks traditional cnns Cnns that have fully connected layers at the end, and fully convolutional networks (fcns) They are only made of convolutional layers (and subsampling and upsampling layers), so they do not contain fully connected layers with traditional cnns, the inputs always need. 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 There are input_channels * number_of_filters sets of weights, each of which describe a convolution kernel So the diagrams showing one set of weights per input channel for each filter are correct. Which two traffic types require delay sensitive delivery (choose two.) email web f?? voice video