In a Multi-layer Perception, every node on the input layer Applies an activation

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In a Multi-layer Perception, every node on the input layer Applies an activation function to a feature of the input feature vector Applies an activation function to the weighted sum of features of the input feature vector Passes on the feature values from the input feature vector to the lint hidden layer Has a fined (constant) weight multiplier A Multi-layer Perception with more than _______ hidden layers can be called a Deep Neural Network. Zero One Two Ten There are several problems that are inherent to Deep Neural Networks and were solved through multiple techniques in recent years. Which one below is not one of those problems? Vanishing gradients Extremely high memory requirements Extremely high training time Severe over-fitting of the training set In drop-out which it the most popularly used regularization technique for Deep Neural Networks. Every neuron will eventually be dropped out during framing Every neuron has a different probability of being dropped during each framing step Some neurons have a higher probability than other neurons of being dropped during each training step Every neuron has the tame probability of being dropped during each training step The Rectified Linear Unit (ReLU) is a commonly used activation function for neurons in Deep Neural Networks. (True/False) A convolutional layer of the Convolutional Neural Network (CNN) performs convolution of a matrix over different parts (patches) of an image to produce a (an) Larger image as output from that layer Smaller image as output from that layer Sharper image as output from that layer Average image as output from that layer A pooling layer of the Convolutional Neural Network (CNN) performs a pooling operation over different image parts (patches). This pooling operation it commonly the The max pooling The min pooling The sum pooling The absolute pooling

Explanation / Answer

2) A multilayer perceptron with more than____hidden layers can be called a deep neural network

b)One

7) A pooling layer of the convolutional neural network(CNN) performs a pooling operation over different image parts(patches). this pooling operation is commonly the

a) The max pooling

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