# Deep Learning IIT Ropar Week 8 Nptel Assignment Answers

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## Table of Contents

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

**Which of the following activation functions is not zero-centered?**

A) Sigmoid

B) Tanh

C) ReLU

D) Softmax

**Answer:** C) ReLU

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

**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

**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

**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

**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.

**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**

**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

**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

**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

**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 wewish 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

**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?**

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

**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 taskStatement 2: For a transfer learning task, last few layers are more generally transferred to another taskWhich 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 networkStatement 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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