[Week 3] NPTEL Deep Learning – IIT Ropar Assignment Answer 2023

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NPTEL Deep Learning – IIT Ropar Assignment Answer

NPTEL Deep Learning - IIT Ropar Assignment Answers

NPTEL Deep Learning – IIT Ropar Week 3 Assignment Answer 2023

1. Which of the following statements about backpropagation is true?

  • It is used to optimize the weights in a neural network.
  • It is used to compute the output of a neural network.
  • It is used to initialize the weights in a neural network.
  • It is used to regularize the weights in a neural network.
Answer:- a

2. Let y be the true class label and p be the predicted probability of the true class label in a binary classification problem. Which of the following is the correct formula for binary cross entropy?

Answer:- a

3. Let yi�� be the true class label of the i�-th instance and pi�� be the predicted probability of the true class label in a multi-class classification problem. Write down the formula for multi-class cross entropy loss.

Answer:- For Answer Click Here

4. Can cross-entropy loss be negative between two probability distributions?

  • Yes
  • No
Answer:- For Answer Click Here

5. Let p� and q� be two probability distributions. Under what conditions will the cross entropy between p� and q� be minimized?

  • p�=q�
  • All the values in p� are lower than corresponding values in q�
  • All the values in p� are lower than corresponding values in q�
  • p� = 0 [0 is a vector]
Answer:- For Answer Click Here

6. Which of the following is false about cross-entropy loss between two probability distributions?
It is always in range (0,1)
It can be negative.
It is always positive.
It can be 1.

Answer:- For Answer Click Here

7. The probability of all the events x1,x2,x2….xn
in a system is equal(n>1
). What can you say about the entropy H(X)
of that system?(base of log is 2)

  • H(X)≤1
  • H(X)=1
  • H(X)≥1
  • We can’t say anything conclusive with the provided information.
Answer:- For Answer Click Here

8. Suppose we have a problem where data x
and label y
are related by y=x4+1
. Which of the following is not a good choice for the activation function in the hidden layer if the activation function at the output layer is linear?

  • Linear
  • Relu
  • Sigmoid
  • Tan−1(x)
Answer:- For Answer Click Here

9. We are given that the probability of Event A happening is 0.95 and the probability of Event B happening is 0.05. Which of the following statements is True?

  • Event A has a high information content
  • Event B has a low information content
  • Event A has a low information content
  • Event B has a high information content
Answer:-For Answer Click Here

10. Which of the following activation functions can only give positive outputs greater than 0?

  • Sigmoid
  • ReLU
  • Tanh
  • Linear
Answer:- For Answer Click Here

NPTEL Deep Learning – IIT Ropar Week 2 Assignment Answer 2023

1. What is the range of the sigmoid function σ(x)=1/1+e−x?

  • (−1,1)
  • (0,1)
  • −∞,∞)
  • (0,∞)
Answer :- Click Here

2. What happens to the output of the sigmoid function as |x| very small?

  • The output approaches 0.5
  • The output approaches 1.
  • The output oscillates between 0 and 1.
  • The output becomes undefined.
Answer :- Click Here

3. Which of the following theorem states that a neural network with a single hidden layer containing a finite number of neurons can approximate any continuous function?

  • Bayes’ theorem
  • Central limit theorem
  • Fourier’s theorem
  • Universal approximation theorem
Answer :- Click Here

4. We have a function that we want to approximate using 150 rectangles (towers). How many neurons are required to construct the required network?

  • 301
  • 451
  • 150
  • 500
Answer :- Click Here

5. A neural network has two hidden layers with 5 neurons in each layer, and an output layer with 3 neurons, and an input layer with 2 neurons. How many weights are there in total? (Dont assume any bias terms in the network)

Answer :- Click Here

6. What is the derivative of the ReLU activation function with respect to its input at 0?

  • 0
  • 1
  • −1
  • Not differentiable
Answer :- Click Here

7. Consider a function f(x)=x3−3x2+2. What is the updated value of xafter 3rd iteration of the gradient descent update, if the learning rate is 0.10.1 and the initial value of x is 4?

Answer :- Click Here

8. Which of the following statements is true about the representation power of a multilayer network of sigmoid neurons?

  • A multilayer network of sigmoid neurons can represent any Boolean function.
  • A multilayer network of sigmoid neurons can represent any continuous function.
  • A multilayer network of sigmoid neurons can represent any function.
  • A multilayer network of sigmoid neurons can represent any linear function.
Answer :- Click Here

9. How many boolean functions can be designed for 3 inputs?

  • 65,536
  • 82
  • 56
  • 64
Answer :- Click Here

10. How many neurons do you need in the hidden layer of a perceptron to learn any boolean function with 6 inputs? (Only one hidden layer is allowed)

  • 16
  • 64
  • 16
  • 32
Answer :- Click Here

NPTEL Deep Learning – IIT Ropar Week 1 Assignment Answer 2023

1. The table below shows the temperature and humidity data for two cities. Is the data linearly separable?
[Week 3] NPTEL Deep Learning - IIT Ropar Assignment Answer 2023

  • Yes
  • No
  • Cannot be determined from the given information
Answer :- Yes

2. What is the perceptron algorithm used for?

  • Clustering data points
  • Finding the shortest path in a graph
  • Classifying data
  • Solving optimization problems
Answer :- Classifying data

3. What is the most common activation function used in perceptrons?

  • Sigmoid
  • ReLU
  • Tanh
  • Step
Answer :- Click Here

4. Which of the following Boolean functions cannot be implemented by a perceptron?

  • AND
  • OR
  • XOR
  • NOT
Answer :- Click Here

5. We are given 4 points in R2 say, x1=(0,1),x2=(−1,−1),x3=(2,3),x4=(4,−5).Labels of x1,x2,x3,x4 are given to be −1,1,−1,1 We initiate the perceptron algorithm with an initial weight w0=(0,0) on this data. What will be the value of w0 after the algorithm converges? (Take points in sequential order from x1 to x)( update happens when the value of weight changes)

  • (0,0)
  • (−2,−2)
  • (−2,−3)
  • (1,1)
Answer :- Click Here

6. We are given the following data:
[Week 3] NPTEL Deep Learning - IIT Ropar Assignment Answer 2023
Can you classify every label correctly by training a perceptron algorithm? (assume bias to be 0 while training)

  • Yes
  • No
Answer :- Click Here

7. Suppose we have a boolean function that takes 5 inputs x1,x2,x3,x4,x5? We have an MP neuron with parameter θ=1. For how many inputs will this MP neuron give output y=1?

  • 21
  • 31
  • 30
  • 32
Answer :- 

8. Which of the following best represents the meaning of term “Artificial Intelligence”?

  • The ability of a machine to perform tasks that normally require human intelligence
  • The ability of a machine to perform simple, repetitive tasks
  • The ability of a machine to follow a set of pre-defined rules
  • The ability of a machine to communicate with other machines
Answer :- Click Here

9. Which of the following statements is true about error surfaces in deep learning?

  • They are always convex functions.
  • They can have multiple local minima.
  • They are never continuous.
  • They are always linear functions.
Answer :- Click Here

10. What is the output of the following MP neuron for the AND Boolean function?

y={1,0,if x1+x2+x3≥1 0, therwise

  • y=1 for (x1,x2,x3)=(0,1,1)
  • y=0 for (x1,x2,x3)=(0,0,1)
  • y=1 for (x1,x2,x3)=(1,1,1)
  • y=0 for (x1,x2,x3)=(1,0,0)
Answer :- Click Here

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