NPTEL Deep Learning – IIT Ropar Week 1 Assignment Answers 2024
1. Consider the following table, where x1 and x2 are features and y is a label
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Assume that the elements in w are initialized to zero and the perception learning algorithm is used to update the weights w. If the learning algorithm runs for long enough iterations, then
- The algorithm never converges
- The algorithm converges (i.e., no further weight updates) after some iterations
- The classification error remains greater than zero
- The classification error becomes zero eventually
Answer :- b, d
2. In the perceptron model, the weight w vector is perpendicular to the linear decision boundary at all times.
- True
- False
Answer :- a
3. What is the perceptron algorithm used for?
- Clustering data points
- Classifying data
- Solving optimization problems
- Finding the shortest path in a graph
Answer :- Click Here
Answer :- Click Here
5. Which of the following Boolean functions can be implemented using a perceptron?
- NOR
- NAND
- NOT
- XOR
Answer :-
6. Which of the following threshold values of MP neuron implements AND Boolean function? Assume that the number of inputs to the neuron is 7 and the neuron does not have any inhibitory inputs.
- 1
- 3
- 6
- 7
- 8
Answer :-
7. Suppose we have a boolean function that takes 4 inputs x1,x2,x3,x4? We have an MP neuron with parameter θ=3. For how many inputs will this MP neuron give output y=1?
- 5
- 4
- 1
- 16
Answer :-
8.
- x1=−1
- x1=1
- x2=−1
- x2=1
Answer :- Click Here
Answer :-
10. Which Boolean function with two inputs x1 and x2 is represented by the following decision boundary? (Points on boundary or right of the decision boundary to be classified 1)
- AND
- OR
- XOR
- NAND
Answer :-
11.
Answer :-
12. Suppose we have a boolean function that takes 4 inputs x1, x2, x3, x4? We have an MP neuron with parameter θ=2. For how many inputs will this MP neuron give output y=1?
- 11
- 21
- 15
- 8
Answer :-
13. We are given the following data:
Can you classify every label correctly by training a perceptron algorithm? (assume bias to be 0 while training)
- Yes
- No
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14. We are given the following dataset with features as (x1,x2) and y as the label (-1,1). If we apply the perception algorithm on the following dataset with w initialized as (0,0). What will be the value of w when the algorithm converges? (Start the algorithm from (2,2)
- (-2,2)
- (2,1)
- (2,-1)
- None of These
Answer :-
15. Consider points shown in the picture. The vector w is (-1,0). As per this weight vector, the Perceptron algorithm will predict which classes for the data points x1 and x2.
- x1=1
- x2=1
- x1=-1
- x2=-1
Answer :-
16. Given an MP neuron with the inputs as x1,x2,x3,x4,x5 and threshold θ=3 where x5 is inhibitory input. For input (1,1,1,0,1) what will be the value of y?
- y=0
- y=1since θ≥3
- y=1/2
- Insufficient information
Answer :-
17. An MP neuron takes two inputs x1 and x2. Its threshold is θ=0. Select all the boolean functions this MP neuron may represent.
- AND
- NOT
- OR
- NOR
Answer :-
18. What is the output of a perceptron with weight vector w=[2 −3 1] and bias b=−2 when the input is x=[10−1]?
- 0
- 1
- -1
- 2
Answer :-
19. What is the ”winter of AI” referring to in the history of artificial intelligence?
- The period during winter when AI technologies are least effective due to cold temperatures
- A phase marked by decreased funding and interest in AI research.
- The season when AI algorithms perform at their peak efficiency.
- A period characterized by rapid advancements and breakthroughs in AI technologies
Answer :- Click Here
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