NPTEL Deep Learning Week 6 Assignment Solutions
NPTEL Deep Learning Week 6 Assignment Answers 2023
1. Which of the following is FALSE about PCA and Autoencoders?
a. PCA works well with non-linear data but Autoencoders are best suited for linear data
b. Output of both PCA and Autoencoders is lossy
c. Both PCA and Autoencoders can be used for dimensionality reduction
d. None of the above
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2. Which of the following is not true for PCA? Tick all the options that are correct.
a. Rotates the axes to lie along the principal components
b. Is calculated from the covariance matrix
c. Removes some information from the data
d. Eigenvectors describe the length of the principal components
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3.
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4.
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5. Suppose a neural network has 3 input nodes, a, b, c. There are 2 neurons, X and F. X = a+ 2b+4c and F = 2X + 1. What is the output F when input (a, b, c) = (-6, 1, 2).
a. 5
b. 4
C. 9
d. 8
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6. Suppose a neural network has 3 input nodes, a, b, c. There are 2 neurons, X and F. X = a+ 2b+4c and F = 2X + 1. What is the gradient of F with respect to a, b and c? Assume, (a, b, c) = (-6, 1, 2).
а. (2,4, 8)
b. (1, 2, 4)
c. (-1, -2, -4)
d. (2, 2, 4)
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7. A single hidden and no-bias autoencoder has 100 input neurons and 10 hidden neurons. What will be the number of parameters associated with this autoencoder?
a. 1000
b. 2000
c. 2110
d. 1010
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8.
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9.
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10. Which of the following two vectors can form the first two principal components?
a. {2;3; 1} and {3; 1; -9}
b. {24; 1} and {-2; 1; -8}
c. {2;3;1} and {-3; 1; -9?
d. {2;3; -1} and {3; 1; -9}
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