B.TechSemester 52022-23Machine Learning TechniquesKCS055

Machine Learning Techniques (KCS055) - AKTU Question Paper 2022-23

B.Tech · Semester 5 · Free PDF Download

This is the official AKTU Machine Learning Techniques Previous Year Question Paper for B.Tech Semester 5, academic session 2022-23. Published by Dr. A.P.J. Abdul Kalam Technical University (AKTU/UPTU), Lucknow. Free PDF download — no login required.

Course:B.Tech

Semester:Semester 5

Session:2022-23

University:AKTU / UPTU

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Questions Asked in 2022-23

Machine Learning Techniques (KCS055) — complete question paper

Section AAttempt all questions in brief. 2*10 = 20

a
Discuss model representation of artificial neuron
b
Explain general to specific ordering hypothesis in concept learning
c
Discuss support vectors in SVM
d
Compare Artificial Intelligence and Machine Learning
e
Discuss reinforcement learning
f
Illustrate the advantages of instance-based learning techni ques over other machine learning techniques
g
Differentiate between Gradient Descent and Stochastic Gradi ent Descent
h
Compare ANN and Bayesian network. (i) Illustrate Markov decision model. (j) Differentiate between Q learning and Deep Learning

Section BAttempt any three of the following: 10*3 = 30

a
Explain supervised and unsupervised learning techniques
b
Discuss linear regression and logistic regression in detail
c
Describe the following concepts in decision tree in detail: (i) Avoiding overfitting in decision tree. (ii) Incorporating continuous valued attributes
d
Explain various types of activation functions with examples
e
Illustrate the pro cess of Q-learning and discuss the following terms: (i) Q-values or action value (ii) Rewards and Episode (iii) Temporal difference or TD update

Section CAttempt any one part of the following: 10*1 = 10

a
Illustrate the various areas in which you can apply machine learning
b
Compare regression, classification and clustering in machin e learning along with suitable real- life applications
a
Discuss the role of Bayes theorem in machine learning. How naive Bayes algorithm is different from Bayes theorem?
b
Explain hyperplane (decision boundary) in SVM. Categorize v arious popular kernels associated with SVM
a
Demonstrate K-Nearest Neighbors algorithm for classificatio n with the help of an example
b
Explain Instance based learning. Compare locally weighted r egression and radial basis function networks
a
Explain the different layers used in convolutional neural n etwork with suitable examples
b
Illustrate backpropagation algorithm by assuming the traini ng rules for output unit weights and Hidden Unit weights
a
Explain various types of reinforcement learning techniques with suitable examples
b
How to Identify the reproduction cycle of genetic algorithm ? Explain with suitable example

Question text is extracted from the official AKTU question paper PDF above. Hindi translations are omitted — every question is printed in English in the original paper. Last verified: 2026-08-23.

Repeated Questions — KCS055

Questions that appeared in more than one session, found by comparing 3 years of Machine Learning Techniques papers (2021-22, 2022-23, 2023-24)

Discuss support vectors in SVM