B.TechSemester 62024-25Machine Learning TechniquesBCDS062

Machine Learning Techniques (BCDS062) - AKTU Question Paper 2024-25

B.Tech · Semester 6 · Free PDF Download

This is the official AKTU Machine Learning Techniques Previous Year Question Paper for B.Tech Semester 6, academic session 2024-25. Published by Dr. A.P.J. Abdul Kalam Technical University (AKTU/UPTU), Lucknow. Free PDF download — no login required.

Course:B.Tech

Semester:Semester 6

Session:2024-25

University:AKTU / UPTU

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Questions Asked in 2024-25

Machine Learning Techniques (BCDS062) — complete question paper · 70 marks · 3 Hours

Section AAttempt all q u e s t i o n s i n b r i e f . 02 x 7 = 14

a
Differentiate between supervi sed and unsupervised learning
b
What is the role of the hypot hesis in a learning system?
c
Define hyper plane in the context of SVM
d
Differentiate between linear and logistic regression
e
What is inductive bias?
f
What is gradient descent?
g
Define the Markov Decision Process (MDP)

Section BAttempt any three o f t h e f o l l o w i n g : 07 x 3 = 21

a
Compare Naïve Bayes classifi er and Bayesian belief networks. 1 K 2
b
Discuss the properties that make SVM effective for high-dime nsional data with example
c
Explain how k-NN works. What are its advantages and limitati ons?
d
Describe the basic architect ure of a convolution neural netw ork (CNN) with help of diagram
e
Explain the GA cycle of rep roduction with a neat diagram

Section CAttempt any one p a r t o f t h e f o l l o w i n g : 07 x 1 = 07

a
How Machine Learning algorithms help in detecting fraudulent activities in finance sector? Also give some real-time software used
b
Compare regression, classifica tion and clustering in machine learning along with suitable real-life applications
a
Discuss entropy and information gain in detail. Why are they important in decision tree learning? Illustrate with a numerical example
b
Discuss the concept of Radial Basis Function (RBF) networks. Provide the mathematical formulation and architecture
a
Explain the working of insta nce-based learning. Use diagrams to show how classification is done using k-NN
b
Explain the concept of SVM ker nels. Compare different SVM kernels with mathematical formulation and application suitability. Also, exp lain how SVM determines the optimal hyper plane
a
Explain the architecture and functioning of a Multilayer Per ception (MLP). How does it differ from a single-layer perceptron?
b
Discuss the concept of CNN architecture. Explain the role of different layers such as convolution, pooling, activation, and fully connected layers
a
What is Deep Q-learning? How does it improve over traditiona l Q- learning? Explain with an architecture diagram
b
Compare Genetic Algorithms and Reinforcement Learning in ter ms of learning paradigm, memory, and exploration strategy

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.

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