Which of the following is a good test dataset characterstic? b. Large enough to yield meaningful...

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Which of the following is a good test dataset characterstic? b. Large enough to yield meaningful results c. Is representative of the dataset as a whole d. Both A and B e. None of the above What is a distinguishing feature of a Convolutional Neural Network? a. The ability to analyze information and make a prediction. b. Creating algorithms that allow decisions to be made about various inputs. c. Training a model to recognize patterns. d. Passing data through layers of transformation and analysis to make a prediction. The input image has been converted into a matrix of size 28 X 28 and a kernel/filter of size 7 X with a stride of 1. What will be the size of the convoluted matrix? 7X7 21 X 21 c. 22 X 22 d. 28 X 28 a. b. Determining the weight and bias of each neuron is one the most important steps in a Deep Learning Network,. If you can somehow get the correct value of weights and bias for each neuron, you can approximate any function. What would be the best way to approach this? a. Try to estimate the correct values off-line and assign these values. b. Search every possible combination of weights and biases till you get the best value c. Iteratively check that after assigning a value how far you are from the best values, and slightly change the assigned values values to make them better d. All of these You have trained a computer vision model to recognize pictures of cats. It works very well except when shown a hairless cat, which it does not classify at all. What might be the problem? a. b. C. d. Poor image quality. The training data did not feature any pictures of hairless cats. The computer vision model is flawed The training data did not have enough cat images. Which of the following is a good test dataset characterstic? b. Large enough to yield meaningful results c. Is representative of the dataset as a whole d. Both A and B e. None of the above What is a distinguishing feature of a Convolutional Neural Network? a. The ability to analyze information and make a prediction. b. Creating algorithms that allow decisions to be made about various inputs. c. Training a model to recognize patterns. d. Passing data through layers of transformation and analysis to make a prediction. The input image has been converted into a matrix of size 28 X 28 and a kernel/filter of size 7 X with a stride of 1. What will be the size of the convoluted matrix? 7X7 21 X 21 c. 22 X 22 d. 28 X 28 a. b. Determining the weight and bias of each neuron is one the most important steps in a Deep Learning Network,. If you can somehow get the correct value of weights and bias for each neuron, you can approximate any function. What would be the best way to approach this? a. Try to estimate the correct values off-line and assign these values. b. Search every possible combination of weights and biases till you get the best value c. Iteratively check that after assigning a value how far you are from the best values, and slightly change the assigned values values to make them better d. All of these You have trained a computer vision model to recognize pictures of cats. It works very well except when shown a hairless cat, which it does not classify at all. What might be the problem? a. b. C. d. Poor image quality. The training data did not feature any pictures of hairless cats. The computer vision model is flawed The training data did not have enough cat images.

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Answers i Answer d Explanation Test data set should big enough to calculate models performance and i... View the full answer