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Gujarat Technological UniversitySummer 2025 Examination

GTU 3171617 Applied Machine Learning Summer 2025 Paper Solution & PDF

B.E. · IT Engineering · Semester 7 · Subject Code: 3171617
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Total Marks70 MarksExternal theory exam
Passing Marks23 Marks33% minimum cutoff
Exam Duration2.5 Hours2:30 PM – 5:00 PM
Paper Structure5 QuestionsWith internal OR choices
Jump toQ1Q2Q3Q4Q5

Question 1

14 MarksMedium
(a)

Define machine learning. Enlist any four tools and technologies of machine learning.

3 Marks
(b)
Define the following terms:
i)Event
ii)Sample Space
iii)Random Variable
iv)Inductive bias
4 Marks
(c)

For preparation of the exam, a student knows that one question is to be solved in the exam which is either of types A, B, or C. The probabilities of A, B, or C appearing in the exam are 30%, 20%, and 50% respectively. During the preparation, the student solved 9 of 10 problems of type A, 2 of 10 problems of type B, and 6 of 10 problems of type C. (i) What is the probability that the student will solve the problem of the exam?(ii) Given that the student solved the problem, what is the probability that it was of type A?

7 Marks

Question 2

14 MarksMedium
(a)
Explain the various methods to perform cross validation.
3 Marks
(b)
Explain Monte Carlo Approximation with suitable example.
4 Marks
(c)

According to the U.S. Census Bureau, approximately 6% of all workers in Jackson, Mississippi, are unemployed. In conducting a random telephone survey in Jackson, what is the probability of getting two or fewer unemployed workers in a sample of 20?

7 Marks
OR OPTION
(c)

A study is conducted in a company that employs 800 engineers. A random sample of 50 engineers reveals that the average sample age is 34.3 years. Historically, the population standard deviation of the age of the company’s engineers is approximately 8 years. Construct a 98% confidence interval to estimate the average age of all the engineers in this company.

7 Marks

Question 3

14 MarksMedium
(a)
Discrete Distribution Vs Continuous Distribution.
3 Marks
(b)
Write short note on Bayesian Belief Network.
4 Marks
(c)

Suppose you have a population of test scores for a large group of students. The population's mean test score is 75, and the population's standard deviation is

10You take random samples of 30 students' test scores from this population.

Calculate the following:

aThe mean and standard deviation of the sample means.
bThe probability that the sample mean of one of your samples is greater than
78
cThe probability that the sample mean of one of your samples is between 72 and 78. Use the Central Limit Theorem to solve this problem.
7 Marks
OR OPTION
(a)
Enlist the factors determining the effectiveness of SVM.
3 Marks
(b)
Explain Bays theorem with example.
4 Marks
(c)

An antibiotic resistance test (random variable T) has 1% false positives (i.e. 1% of those not resistance to an antibiotic show positive result in the test) and 5% false negatives (i.e. 5% of those actually resistant to an antibiotic test negative). Let us assume that 2% of those tested are resistant to antibiotics. Determine the probability that somebody who tests positive is actually resistant (random variable D).

7 Marks

Question 4

14 MarksMedium
(a)
Discuss OOB error and variable importance in random forest.
3 Marks
(b)
Explain with suitable example.
i)Multivariate regression
ii)Logistic regression
4 Marks
(c)

Explain the use of association rule mining. Write and explain the steps of Apriori algorithm.

7 Marks
OR OPTION
(a)

Define reinforcement learning. Explain the concept of penalty and reward in reinforcement learning.

3 Marks
(b)
Define and explain MLE and MAP.
4 Marks
(c)

Define the following terms

aSample error
bTrue error
cPrecision
dExpected value e. Variance f. Standard Deviation g. Recall
7 Marks

Question 5

14 MarksMedium
(a)
Write short note on Adversarial Attacks.
3 Marks
(b)
Define Perceptron. Explain its working.
4 Marks
(c)
aDefine RNN.
bEnlist 4 applications of RNN.
cExplain working of RNN.
7 Marks
OR OPTION
(a)
Write short note on GAN with its architecture.
3 Marks
(b)

Enlist and explain various hyper parameters which are being tuned for improving the deep learning model.

4 Marks
(c)
aDefine CNN.
bEnlist 4 applications of CNN.
cExplain working of CNN.
7 Marks
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About this Examination Paper & Attribution

Official Gujarat Technological University (GTU) examination paper and step-by-step solutions for Applied Machine Learning (Summer 2025, B.E. · IT Engineering, Sem 7). Features complete 70-mark regular & remedial examination pattern, official marking distribution across all 5 questions, and direct 1-click official PDF download.

Transcribed for student exam preparation from Gujarat Technological University official examination archives. Questions, syllabus guidelines, and curriculum marking schemes remain the intellectual property of Gujarat Technological University.

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