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) — extracted question text

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. Check the original PDF for equations, diagrams and complete wording. Extracted: 2026-08-23.

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