Deep Learning MCQ Questions And Answers

21. Which neural network has only one hidden layer between the input and output?

  1. Deep neural network
  2. Shallow neural network
  3. Recurrent neural networks
  4. Feed-forward neural networks

Answer : B
Explanation: Shallow neural network : The Shallow neural network has only one hidden layer between the input and output and hence, option B is correct.

22. Which of the following library comes with a visualization tool for deep learning?​

  1. Infer.net
  2. Pandas
  3. Matplotlib
  4. None of the above

Answer : A
Explanation: Infer.net is the library that comes with a visualization tool for deep learning. So, option A is correct.

23. Which of the following is well suited for perceptual tasks?

  1. Recurrent neural networks
  2. Feed-forward neural networks
  3. Reinforcement Learning
  4. Convolutional neural networks

Answer : D
Explanation: CNN (Convolutional neural networks) is a multi-layered neural network with a unique architecture designed to extract increasingly complex features of the data at each layer to determine the output. CNNs are well suited for perceptual tasks. So, option D is correct.

24. The number of nodes in the input layer is 10 and the hidden layer is 5. The maximum number of connections from the input layer to the hidden layer are :

  1. More than 50
  2. Less than 50
  3. 50
  4. Can’t say

Answer : C
Explanation: Since MLP is a fully connected directed graph, the number of connections are a multiple of number of nodes in input layer and hidden layer and hence, option C is correct.

25. Which term best defines the process of improving a deep learning model that has already been trained for a particular task using a smaller dataset?

  1. Model initialization
  2. Data augmentation
  3. Transfer learning
  4. Gradient descent

Answer : C
Explanation: The process of improving a deep learning model that has already been trained for a particular task using a smaller dataset is called as Transfer Learning. So, option C is correct.

Data Science MCQ Questions And Answers

26. What is the purpose of A/B testing when deploying a deep learning model?

  1. To compare the model’s accuracy to a random baseline
  2. To evaluate the model’s performance in a real-world setting
  3. To determine the model’s training time
  4. To train multiple models simultaneously

Answer : B
Explanation: A/B testing is used to evaluate a model’s performance in a real-world setting by comparing it to alternative approaches and hence, option B is correct.

27. The input image has been converted into a matrix of size 28 X 28 and a kernel/filter of size 7 X 7 with a stride of 1. What will be the size of the convoluted matrix?

  1. 22×22
  2. 28×28
  3. 19×19
  4. 21×21

Answer : A
Explanation: The size of the convoluted matrix is given by C=((I-F+2P)/S)+1, where C is the size of the Convoluted matrix, I is the size of the input matrix, F the size of the filter matrix and P the padding applied to the input matrix. Here, P=0, I=28, F=7 and S=1. So, the answer is ((28-7+0)/1)+1=22. So, option A is correct.

28. CNN is mostly used when there is an?

  1. Unstructured data
  2. Structured data
  3. Both A and B
  4. None of the above

Answer : A
Explanation: CNN (Convolutional neural networks) is mostly used when there is an unstructured data set (e.g., images) and the practitioners need to extract information from it. So, option A is correct.

29. Deep Learning algorithms are _________ more accurate than machine learning algorithms in image classification.

  1. 31%
  2. 37%
  3. 28%
  4. 41%

Answer : D
Explanation: Deep Learning can outperform traditional method. For instance, deep learning algorithms are 41% more accurate than machine learning algorithm in image classification, 27% more accurate in facial recognition and 25% in voice recognition and hence, option D is correct.

30. In deep learning, what is the role of a loss function?

  1. To normalize input data
  2. To measure the model’s prediction accuracy
  3. To initialize model parameters
  4. To calculate the gradients for optimization

Answer : D
Explanation: In deep learning, the role of a loss function is to calculate the gradients for optimization. So, option D is correct.

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