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WorksheetsBertelsmann AI Track Quiz Initiative #2
Total questions: 10
Worksheet time: 23mins
What do you know about the convolutional term in convolutional neural network (CNN)? Choose all correct answers
It refers to a mathematical operation that produces a high dimensional tensor
It refers to the mathematical function that slides a filter over the input
It breaks down the input feature into smaller parts
The term convolution refers to the mathematical combination of three functions to produce the fourth function
What is the desired output of the CNN layer?
Kernel
Feature map
Decomposed input
Classifier
Why do we need to put fully-connected layers in the end of CNN in the case of MNIST dataset? Choose the best answer
CNN only yield feature map
To improve accuracy even better
MNIST dataset contains a lot of noise
The activation function in CNN is not suitable for a classification task
For which purpose Convolutional Neural Network is used?
It is a multi purpose alghorithm that can be used for Unsupervised Learning.
Mainly to process and analyse digital images, with some success cases involving processing voice and natural language.
It is a multi purpose alghorithm that can be used for Reinforced Learning.
Mainly to process and analyse financial models, predicting future trends.
What is the biggest advantage utilizing CNN?
Little dependence on pre-processing, decreasing the needs of human effort developing its functionalities.
It is easy to understand and fast to implement.
It has the highest accuracy among all algorithms that predicts images.
It works well both for Supervised and Unsupervised Learning.
Which answer explains better the Pooling?
Creates a pool of data in order to improve the accuracy of the alghorithm predicting images.
It assists in the detection of distorted features, in order to find dominant attributes.
It assists in the detection of features, even if they are distorted, in addition to decreasing the attribute sizes, resulting in decreased computational need.
Decrease the features size, in order to decrease the computional power that are needed.
What do Shared Weights mean in CNN? Choose the best answer
It calculates the feature´s weights and compares with other algorithms in order to find the best parameters.
Sharing weights among the features, make it easier and faster to CNN predict the correct image.
Forcing the neurons of one layer to share weights, the forward pass becomes the equivalent of convolving a filter over the tensor to produce a new tensor.
It means that CNN uses the weights of each feature in order to find the best model to make a prediction, sharing the results and returning the average.
What type of cost function is used in a convolutional neural network?
Categorical cross-entropy
RMSE
Maximum Likelihood
It depends on the task.
Suppose we do convolution upon an input image and a kernel, then what is the output of this operation?
-3
-1
1
3
Which researcher below mostly renowned by his/her work in CNN? Choose the best answer
Andrew Ng
Yann LeCun
Geoffrey Hinton
Yoshua Bengio
