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PYQ [Week 1-12] NPTEL Deep Learning – IIT Ropar Assignment Answers 2023
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Deep Learning | Week 8
Course Name: Deep Learning
Course Link: Click Here
These are NPTEL Deep Learning Week 8 Assignment 8 Answers
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
Answer: a. 252×252
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
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
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
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
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
Q10. How many convolution layers are there in a LeNet-5 architecture? a. 2 b. 3 c 4 d. 5
Answer: a. 2
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Deep Learning | NPTEL 2023 | Week 1 Assignment 1 solutions
This set of MCQ(multiple choice questions) focuses on the Deep Learning NPTEL 2023 Week 1 Assignment 1 Solutions .
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NOTE: You can check your answer immediately by clicking show answer button. Deep Learning NPTEL 2023 Week 1 Assignment 1 Solutions” contains 10 questions.
Now, start attempting the quiz.
Deep Learning NPTEL 2023 Week 1 Quiz Solutions
Q1. From a pack of 52 cards, two cards are drawn together at random. What is the probability of both the cards being kings?
a) 1/15 b) 25.57 c) 35/256 d) 1/221
Answer: d) 1/221
Q2. For a two class problem Bayes minimum error classifier follows which of following rule? (The two different classes are ω 1 and ω 2, and input feature vector is x)
a) Choose ω 1 if P( ω 1/x) > P( ω 2/x) b) Choose ω 1 if P( ω 1) > P( ω 2) c) Choose ω 2 if P( ω 1) < P( ω 2) d) Choose ω 2 if P( ω 1/x) > P( ω 2/x)
Answer: a) Choose ω1 if P(ω1/x) > P(ω2/x)
Q3. The texture of the region provides measure of which of the following properties?
a) Smoothness alone b) Coarseness alone c) Regularity alone d) Smoothness, coarseness and regularity
Answer: d) Smoothness, coarseness and regularity
Deep Learning NPTEL 2023 week 1 Assignment Solutions
Q4. Why convolution neural network is taking off quickly in recent times? (Check the options that are true.)
a) Access to large amount of digitized data b) Integration of feature extraction within the training process c) Availability of more computational power d) All of the above
Answer: d) All of the above
Q5. The bayes formula states:
a) posterior = likelihood*prior / evidence b) posterior = likelihood*evidence / prior c) posterior = likelihood * prior d) posterior = likelihood * evidence
Answer: c) posterior = likelihood * prior
Q6. Suppose Fourier descriptor of a shape has K coefficient, and we remove last few coefficient and use only m (m<k) number of coefficient to reconstruct the shape. What will be effect of using truncated Fourier descriptor on the reconstructed shape?
a) We will get a smoothed boundary version of the shape b) We will get only the fine details of the boundary of the shape c) Full shape will be reconstructed without any loss of information d) Low frequency component of the boundary will be removed from contour of the shape
Answer: a) We will get a smoothed boundary version of the shape
Deep Learning NPTEL week 1 Assignment Solutions
Q7. The plot of distance of the different boundary point from the centroid of the shape taken at various direction is known as
a) Signature descriptor b) Polygonal descriptor c) Fourier descriptor d) Convex Hull
Answer: a) Signature descriptor
Q8. If the larger value of gray co-occurrence matrix are concentrated around the main diagonal, then which one of the following will be true?
a) The value of element difference moment will be high b) The value of inverse element difference moment will be high c) The value of entropy will be very low d) None of the above
Answer: d) None of the above
Q9. Which of the following is a Co-occurrence matrix based descriptor
a) Entropy b) Uniformity c) Signature d) Inverse Element difference moment e) All of the above
Answer: d) Inverse Element difference moment
Q10. Consider two class Bayes’ Minimum Risk Classifier. Find the Risk R (a2 | x)
a) 0.42 b) 0.61 c) 0.48 d) 0.39
Answer: b) 0.61
Q1. Pick out the appropriate shape of decision boundary if the number of inputs is three.
a) Point b) Line c) Plane d) Hyperplane
Answer: c) Plane
Q2. Pick out the one in biological neuron that is responsible for receiving signal from other neurons.
a) Dendrite b) Synapse c) Soma d) Axon
Answer: a) Dendrite
Q3. Which of the following is considered as a drawback of Deep Learning?
a) Numerical stability b) Overfitting never occurs c) Sharp minima d) Overfitting always occurs
Answer: c) Sharp minima
Q4. Neurons play a vital role in how humans respond to the outside world. When does this occur?
a) Any one neuron gets activated b) All the neurons of massively parallel interconnected network of neurons are activated. c) Specific set of these neurons fire and relay the information to other neurons d) At least 10% of the total number of neurons in the brain
Answer: c) Specific set of these neurons fire and relay the information to other neurons
Q5. Consider a Mc Culloch Pitts Neuron for which the inputs are x1,x2 and x3. Also, the aggregate function g(x) is an OR function. What is the thresholding parameter for the same?
a) 0 b) 1 c) 2 d) 3
Answer: b) 1
Q6. Which of the following statements are True? Statement I. Mc. Culloch Pitts neuron can be used to represent any boolean function Statement II. If any of the inputs in a Mc. Culloch Pitts Neuron is inhibitory, then output will be zero
a) Only I b) Only II c) Both d) None
Answer: b) Only II
Q7. Pick out the boolean function that is not linearly separable.
a) AND b) OR c) NOR d) XOR
Answer: d) XOR
Q8. In a perceptron learning algorithm, what is the initial value of the weights before the algorithm starts learning?
a) All weights set to zero b) All weights set to one c) All weights assigned random values d) All weights assigned values specific to the application in hand
Answer: c) All weights assigned random values
Q9. What is the condition for convergence of a perceptron learning algorithm?
a) Always converges b) Data is linearly separable c) Data is linearly non-separable d) May or may not converge depending on the data
Answer: b) Data is linearly separable
Q10. Select all the statements that hold TRUE for a Single Perceptron.
a) Inputs are weighted b) Threshold is hand coded c) Only Real inputs are allowed d) Both Real and boolean inputs are allowed e) Can solve only linearly separable data
Answer: a), d), e)
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Deep Learning
| Course Status : | Completed |
| Course Type : | Elective |
| Duration : | 12 weeks |
| Category : | |
| Credit Points : | 3 | Undergraduate/Postgraduate |
| Start Date : | 23 Jan 2023 |
| End Date : | 14 Apr 2023 |
| Enrollment Ends : | 06 Feb 2023 |
| Exam Registration Ends : | 17 Mar 2023 |
| Exam Date : | 30 Apr 2023 IST |
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