B.TechSemester 62022-23Advanced Machine LearningKML-061

Advanced Machine Learning (KML-061) - AKTU Question Paper 2022-23

B.Tech · Semester 6 · Free PDF Download

This is the official AKTU Advanced Machine Learning Previous Year Question Paper for B.Tech Semester 6, 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 6

Session:2022-23

University:AKTU / UPTU

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Questions Asked in 2022-23

Advanced Machine Learning (KML-061) — complete question paper

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

a
What is the role of Inductive Bias in ANN?
b
How do you choose the number of hidden layers and nodes in a multi -layer perceptron?
c
What is Bayesian learning?
d
How can prior knowledge be incorporated into a Bayesian learning model?
e
Explain the concept of pruning in decision tree models
f
Discuss overfitting and underfitting situation in decision tree learning
g
How Reinforcement Learning different from other types of machine learning?
h
Explain the concept of a feedback network in reinforcement learning. (i) What is a random forest? (j) How does a random forest differ from a decision tree model?

Section BAttempt any three of the following: 10x3=30

a
Explain the concept of backpropagation and how it i s used to train a neural network?
b
Explain the concept of Markov Chain Monte Carlo (MC MC) methods in Bayesian learning, and how they are used for parame ter estimation and model selection?
c
How do decision trees compare to other machine lear ning algorithms, such as neural networks or support vector machines?
d
Explain the various learning m odels for reinfor cement learning
e
What is an ensemble in machine learning and how is it used to improve model performance?

Section CAttempt any one part of the following: 10 x1=10

a
Explain the concept of gradient descent and how it is used in backpropagation?
b
What are some real-world applications of multi-laye r perceptron’s and neural networks?
a
How is Bayes theorem used in machine learning? How naive Bayes algorithm is different from Bayes theorem
b
What are some common challenges and limitations of Bayesian networks, and how can these be addressed?
a
How can decision trees be used for both classificat ion and regression problems?
b
List down the attribute selection measures used by the ID3 algorithm to construct a Decision Tree
b
Describe Markov Decision Process in reinforcement learning
b
What are some advantages and disadvantages of using ensemble techniques in machine learning?

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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