NPTEL Deep Learning Week 6 Assignment Answers 2025
1. Suppose a neural network has 3 input nodes, a, b, c. There are 2 neurons, X and Y. X = a+ b and
Y = X * c. What is the gradient of Y with respect to a, b and c? Assume, (a, b, c) = (6, -1, -4).
a. (5, -4, -4)
b. (4,4, -5)
c. (-4, -4, 5)
d. (3, 3,4)
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2.
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3. PCA reduces the dimension by finding a few
a. Hexagonal linear combination
b. Orthogonal linear combinations
c. Octagonal linear combination
d. Pentagonal Linear Combination
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4.
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5. Which of the following is FALSE about PCA and Auto encoders?
a. Both PCA and Auto encoders can be used for dimensionality reduction
b. PCA works well with non-linear data but Auto encoders are best suited for linear data
c. Output of both PCA and Auto encoders is lossy
d. None of the above
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6. What is tre regarding backpropagation rule?
a. It is a feedback neural network
b. Gradient of the final layer of weights being calculated first and the gradient of the first layer of
weights being calculated last
c. Hidden layers is not important, only meant for supporting input and output layer
d. None of the mentioned
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7. Which of the following is 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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8. 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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9. Which of the following two vectors can form the first two principal components?
a. (2;3;1} and (3;1; -9}
b. (2;4;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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10. ets say vectors @ = (2; 4) and b = (n; 1} forms the first two principle components after applying PCA Inder such circumstances, which among the following can be a possible value of n
a. 2
b. -2
c. 0
d. 1
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