Gujarat Technological UniversitySummer 2026 examination

GTU 3171617 Applied Machine Learning Summer 2026 Question Paper & PDF

B.E. · IT Engineering · Semester 7 · Subject code 3171617
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Total
70 marks
To pass
23 marks (33%)
Duration
2.5 Hours 2:30 PM – 5:00 PM
Questions
5 with internal choice
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9 of 25 questions on this paper were also asked in other years. 1 more is a type of question GTU sets again with new data. Each is marked below with the years it appeared.See all 10 repeated 3171617 questions, most asked first

Q.1

14 Marks
(a)
3 marks
Define the Following terms: 1. Hypothesis space 2. Inductive bias
(b)
4 marksAsked in 2 of 2 papers
State Bayes' theorem and explain its formula.

Also asked in Summer 2025 Q3b OR

(c)
7 marksAsked in 2 of 2 papers

Suppose two students train the models in which one uses cross-validation, the other does not. Evaluate which approach is more reliable and why?

Also asked in Summer 2025 Q2a

Q.2

14 Marks
(a)
3 marks
Define the terms : 1. Overfitting 2. Underfitting
(b)
4 marks

Explain how sampling distributions are used in hypothesis testing with a simple example.

(c)
7 marks

A shopkeeper wants to predict whether tomorrow’s sales will be high or low using past data of sales. How can you apply Logistic Regression for this problem?

(c)
7 marks

A University is having student marks data. How to apply a Decision Tree to decide whether a student will pass or fail?

Q.3

14 Marks
(a)
3 marksAsked in 2 of 2 papers
What is hyperparameter tuning?

Also asked in Summer 2025 Q5b OR

(b)
4 marks
Compare CNN and RNN.
(c)
7 marksAsked in 2 of 2 papers

Define adversarial attack in machine learning. Explain how small changes to input data can fool a trained model with any real-world applications example.

Also asked in Summer 2025 Q5a

(a)
3 marksAsked in 2 of 2 papers
Enlist 4 applications of RNN.

Also asked in Summer 2025 Q5c

(b)
4 marks
Differentiate between supervised learning and unsupervised learning.
(c)
7 marksAsked in 2 of 2 papers
Explain the role of Generator and Discriminator in a GAN with a simple example.

Also asked in Summer 2025 Q5a OR

Q.4

14 Marks
(a)
3 marks
What is the difference between classification and regression?
(b)
4 marksAsked in 2 of 2 papers

State the difference between Maximum Likelihood Estimation (MLE) and Maximum A Posteriori Estimation (MAP).

Also asked in Summer 2025 Q4b OR

(c)
7 marks

Define slope in a linear regression. Find the slope of the graph where the lower point on the line is represented as (−3, −2) and the higher point on the line is represented as (2, 2).

(a)
3 marks
Explain the concept of sampling distribution.
(b)
4 marksAsked in 2 of 2 papers
Compare discrete vs continuous distribution with example.

Also asked in Summer 2025 Q3a

(c)
7 marks
Explain in brief back propagation algorithm.

Q.5

14 Marks
(a)
3 marks
Explain role of activation functions in neural networks.
(b)
4 marksSame type asked in 2 of 2 papers

A population consists of six numbers 4,8,12,16,20,24 .consider all samples of size two which can be drawn without replacement from this population. Calculate

i)The Population mean
ii)The population standard deviation

Also asked in Summer 2025 Q3c

(c)
7 marks

Given the 1-D data {2,4,5,10,12,20}, perform one iteration of K-Means clustering with K=2, using initial cluster centers 4 and 12. Assign each data point to the nearest center and compute the updated clusters.

(a)
3 marks
Explain XOR problem in case of a simple perceptron.
(b)
4 marksAsked in 2 of 2 papers

Analyze the working of a Convolutional Neural Network. Compare its performance with a simple feed forward neural network with suitable example

Also asked in Summer 2025 Q5c OR

(c)
7 marks

Evaluate the role of parameter estimation methods in deep neural networks. Which approach is most suitable when data is limited.

More Applied Machine Learning papers

Questions repeat across sessions. Working through two or three papers shows you which topics GTU asks most.

Summer 202570 marks · 5 questions

Other Semester 7 subjects

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2171607
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3171609
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3171610
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About this paper

Official Gujarat Technological University (GTU) examination paper for Applied Machine Learning (Summer 2026, 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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