# Deep Learning MCQs

This section focuses on "Deep Learning" in Data Science. These Data Science Multiple Choice Questions (MCQ) should be practiced to improve the skills required for various interviews (campus interview, walk-in interview, company interview), placements, entrance exams and other competitive examinations.

1. Which of the following is a subset of machine learning?

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2. How many layers Deep learning algorithms are constructed?

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3. The first layer is called the?

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4. RNNs stands for?

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5. Which of the following is/are Common uses of RNNs?

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

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7. CNN is mostly used when there is an?

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

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9. Which of the following is/are Limitations of deep learning?

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10. Deep learning algorithms are _______ more accurate than machine learning algorithm in image classification.

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11. In which of the following applications can we use deep learning to solve the problem?

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12. Which of the following statements is true when you use 1×1 convolutions in a CNN?

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13. 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

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14. 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?

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15. In a simple MLP model with 8 neurons in the input layer, 5 neurons in the hidden layer and 1 neuron in the output layer. What is the size of the weight matrices between hidden output layer and input hidden layer?

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16. Which of the following functions can be used as an activation function in the output layer if we wish to predict the probabilities of n classes (p1, p2..pk) such that sum of p over all n equals to 1?

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17. Assume a simple MLP model with 3 neurons and inputs= 1,2,3. The weights to the input neurons are 4,5 and 6 respectively. Assume the activation function is a linear constant value of 3. What will be the output ?

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18. Which of the following would have a constant input in each epoch of training a Deep Learning model?

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19. Sentiment analysis using Deep Learning is a many-to one prediction task

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20. In CNN, having max pooling always decrease the parameters?

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