Deep Learning – IIT Ropar | Week 1

Session: JULY – DEC 2024

Course name: Deep Learning – IIT Ropar

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These are Deep Learning IIT Ropar Week 1 Assignment 1 Nptel Answers


Q1. Consider the following table, where x1 and x2 are features and y is a label
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: The algorithm converges (i.e., no further weight updates) after some iterations

The classification error becomes zero eventually


Q2. In the perceptron model, the weight w vector is perpendicular to the linear decision boundary at all times.
True
False

Answer: True


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Q3.What is the perceptron algorithm used for?
Clustering data points
Classifying data
Solving optimization problems
Finding the shortest path in a graph

Answer: Classifying data


Q4. Choose the correct input-output pair for the given MP Neuron. f(x)={1,0,if x1+x2+x3>2 0,otherwise
y=1 for (x1,x2,x3)=(0,1,1)
y=0 for (x1,x2,x3)=(0,0,1)
y=1 for (x1,x2,x3)=(0,0,0)
y=1 for (x1,x2,x3)=(1,1,1)
y=0 for (x1,x2,x3)=(1,0,1)

Answer: b)y=0 for (x1,x2,x3)=(0,0,1) , d,)y=1 for (x1,x2,x3)=(1,1,1) ,e) y=0 for (x1,x2,x3)=(1,0,1)


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Q5.Which of the following Boolean functions can be implemented using a perceptron?
NOR
NAND
NOT
XOR

Answer: NOR
NAND
NOT


Q6. 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


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Q7.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: 5


Q8.Consider points shown in the picture. The vector w=[−1−1].As per this weight vector, the Perceptron algorithm will predict which classes for the data points x1 and x2.
x1=−1
x1=1
x2=−1
x2=1

Answer:a) x1=−1, d) x2=1


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Q9.Consider the following table, where x1 and x2 are features (packed into a single vector x=[x1x2]
) and y is a label:

Suppose that the perceptron model is used to classify the data points. Suppose further that the weights w
are initialized to w=[11] .The following rule is used for classification,

2
1
0
Not possible to determine

Answer: 0


Q10.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: OR


Q11.Choose the correct input-output pair for the given MP Neuron.
y={1,ifx1+x2+x3≥2
0, otherwise

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: a),b),c)


Q12.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: 8


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Q13.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

Answer: No


Q14.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: (2,-1)


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Q15.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: x2=1 ,x1=-1


Q16.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=1 since θ≥3
y=1/2
Insufficient information

Answer: y=0


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Q17.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: NOR


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Q18. What is the output of a perceptron with weight vector w=[2−31] and bias b=−2
when the input is x=[10−1]
?
0
1
-1
2

Answer: -1


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Q19 .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: A phase marked by decreased funding and interest in AI research.


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