Deep Learning IIT Ropar Week 8 Nptel Assignment Answers

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Deep Learning IIT Ropar Week 8 Nptel Assignment Answers
Deep Learning IIT Ropar Week 8 Nptel Assignment Answers

Deep Learning IIT Ropar Week 8 Nptel Assignment Answers (July-Dec 2024)


  1. Which of the following activation functions is not zero-centered?
    A) Sigmoid
    B) Tanh
    C) ReLU
    D) Softmax

Answer: C) ReLU


  1. What is the gradient of the sigmoid function at saturation?
    Answer: 0

  1. Given a neuron initialized with weights w1=1.5, w2=0.5, and inputs x1=0.2, x2=−0.5, calculate the output of a ReLU neuron.
    Answer: 0.05

  1. How does pre-training prevent overfitting in deep networks?
    A) It adds regularization
    B) It initializes the weights near local minima
    C) It constrains the weights to a certain region
    D) It eliminates the need for fine-tuning

Answer: D) It eliminates the need for fine-tuning


  1. We train a feed-forward neural network and notice that all the weights for a particular neuron are equal. What could be the possible causes of this issue?
    A) Weights were initialized randomly
    B) Weights were initialized to high values
    C) Weights were initialized to equal values
    D) Weights were initialized to zero

Answer: A) Weights were initialized randomly
C) Weights were initialized to equal values


  1. Which of the following best describes the concept of saturation in deep learning?
    A) When the activation function output approaches either 0 or 1 and the gradient is close to zero.
    B) When the activation function output is very small and the gradient is close to zero.
    C) When the activation function output is very large and the gradient is close to zero.
    D) None of the above.
See also  Deep Learning | Week 9

Answer: A) When the activation function output approaches either 0 or 1 and the gradient is close to zero.


These are Deep Learning IIT Ropar Week 8 Nptel Assignment Answers


  1. Which of the following is true about the role of unsupervised pre-training in deep learning?
    A) It is used to replace the need for labeled data
    B) It is used to initialize the weights of a deep neural network
    C) It is used to fine-tune a pre-trained model
    D) It is only useful for small datasets

Answer: B) It is used to initialize the weights of a deep neural network


  1. Which of the following is an advantage of unsupervised pre-training in deep learning?
    A) It helps in reducing overfitting
    B) Pre-trained models converge faster
    C) It improves the accuracy of the model
    D) It requires fewer computational resources

Answer: B) Pre-trained models converge faster


  1. What is the main cause of the Dead ReLU problem in deep learning?
    A) High variance
    B) High negative bias
    C) Overfitting
    D) Underfitting

Answer: B) High negative bias


  1. What is the main cause of the symmetry breaking problem in deep learning?
    A) High variance
    B) High bias
    C) Overfitting
    D) Equal initialization of weights

Answer: D) Equal initialization of weights


These are Deep Learning IIT Ropar Week 8 Nptel Assignment Answers

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Deep Learning Week 8 Nptel Assignment Answers (Apr-Jun 2023)


Q1. 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 such that the sum of p over all n equals to 1?

a. Softmax
b. RelU
c. Sigmoid
d. Tanh

Answer: a. Softmax


Q2. The input image has been converted into a matrix of size 256 X 256 and a kernel/filter of size 5×5 with a stride of 1 and no padding. What will be the size of the convoluted matrix?
a. 252×252
b. 3×3
c 254×254
d. 256×256

See also  Deep Learning IIT Ropar Week 3 Nptel Answers

Answer: a. 252×252


These are NPTEL Deep Learning Week 8 Assignment Answers


Q3. What will be the range of output if we apply ReLU non-linearity and then Sigmoid Nonlinearity subsequently after a convolution layer?
a. [1,1]
b. [0,1]
c. [0.5,1]
d. [1,-0.5]

Answer: c. [0.5,1]


Q4. The figure below shows image of a face which is input to a convolutional neural net and the other three images shows different levels of features extracted from the network. Can you identify from the following options which one is correct?

image 40

a. Label 3: Low-level features, Label 2: High-level features, Label 1: Mid-level features
b. Label 1: Low-level features, Label 3: High-level features, Label 2: Mid-level features
c. Label 2: Low-level features, Label 1: High-level features, Label 3: Mid-level features
d. Label 3: Low-level features, Label 1: High-level features, Label 2: Mid-level features

Answer: b. Label 1: Low-level features, Label 3: High-level features, Label 2: Mid-level features


These are NPTEL Deep Learning Week 8 Assignment Answers


Q5. Suppose you have 8 convolutional kernel of size 5 x 5 with no padding and stride 1 in the first layer of a convolutional neural network. You pass an input of dimension 228 x 228 x 3 through athis layer. What are the dimensions of the data which the next layer will receive?
a. 224x224x3
b. 224x224x8
c. 226x226x8
d. 225x225x3

Answer: b. 224x224x8


Q6. What is the mathematical form of the Leaky RelU layer?
a. f(x)=max(0,x)
b. f(x)=min(0,x)
c. f(x)=min(0, ax), where a is a small constant
d. f(x)=1(x<0)(ax)+1(x>=0)(x), where a is a small constant

Answer: d. f(x)=1(x<0)(ax)+1(x>=0)(x), where a is a small constant


These are NPTEL Deep Learning Week 8 Assignment Answers


Q7. The input image has been converted into a matrix of size 224 x 224 and convolved with a kernel/filter of size FxF with a stride of s and padding P to produce a feature map of dimension 222×222. Which among the following is true?
a. F=3×3,s=1,P=1
b. F=3×3,s=0, P=1
c. F=3×3,s=1,P=0
d. F=2×2,s=0, P=0

See also  Deep Learning | Week 4

Answer: c. F=3×3,s=1,P=0


These are NPTEL Deep Learning Week 8 Assignment Answers


Q8. Statement 1: For a transfer learning task, lower layers are more generally transferred to another task
Statement 2: For a transfer learning task, last few layers are more generally transferred to another task
Which of the following option is correct?

a. Statement 1 is correct and Statement 2 is incorrect
b. Statement 1 is incorrect and Statement 2 is correct
c. Both Statement 1 and Statement 2 are correct
d. Both Statement 1 and Statement 2 are incorrect

Answer: a. Statement 1 is correct and Statement 2 is incorrect


These are NPTEL Deep Learning Week 8 Assignment Answers


Q9. Statement 1: Adding more hidden layers will solve the vanishing gradient problem for a 2-layer neural network
Statement 2: Making the network deeper will increase the chance of vanishing gradients.

a. Statement 1 is correct
b. Statement 2 is correct
c. Neither Statement 1 nor Statement 2 is correct
d. Vanishing gradient problem is independent of number of hidden layers of the neural network.

Answer: b. Statement 2 is correct


These are NPTEL Deep Learning Week 8 Assignment Answers


Q10. How many convolution layers are there in a LeNet-5 architecture?
a. 2
b. 3
c 4
d. 5

Answer: a. 2


These are NPTEL Deep Learning Week 8 Assignment Answers

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