B.TechSemester 72024-25Machine LearningKME074

Machine Learning (KME074) - AKTU Question Paper 2024-25

B.Tech · Semester 7 · Free PDF Download

This is the official AKTU Machine Learning Previous Year Question Paper for B.Tech Semester 7, 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 7
Session:2024-25
University:AKTU / UPTU

Rate this paper

Questions Asked in 2024-25

Machine Learning (KME074) — complete question paper · 100 marks · 3 Hours

Section AAttempt all questions in brief. 2 x 10 = 20
  • a
    Explain the terms Artificial Int elligence (AI), Machine Learni ng (ML), and Deep Learning
  • b
    What are the three main types of machine learning? Explain eac h type with an example
  • c
    What is the implication of the use of a single learning rate ( η) for all features (xj) in gradient descent optimization?
  • d
    Differentiate between training data and testing data in machin e learning
  • e
    Describe dimension reduction in machine learning
  • f
    Define hierarchical clustering
  • g
    Explain the term 'loss function' in deep learning
  • h
    What is the meaning of Overfitt ing in Machine learning? 4 K1 i. Use a genetic algorithm to optimize a scheduling problem and e xplain each step. j. Define the term "kernel" in the context of Gaussian processes. 5 K 1
Section BAttempt any three of the following: 3 x 10 = 30
  • a
    Describe artificial intelligence (AI) and its potential impa ct on modern industries
  • b
    What is the purpose of support vector machines (SVM), and ho w do they work?
  • c
    What is the expectation-maximization algorithm? Provide a br ief overview
  • d
    Discuss the challenges and li mitations of the Backpropagatio n algorithm in neural network training
  • e
    Define Hidden Markov Models (HMM) and their applications
Section CAttempt any one part of the following: 1 x 10 = 10
  • a
    What are the essential steps involved in designing a learnin g system? Explain each step briefly
  • b
    Explain the applications of machine learning in mechanical engineering. Provide at least three use cases
  • a
    Explain Bayesian Decision Theory
  • b
    What are bias and variance in machine learning? How do they affect model performance?
  • a
    Define Principal Component Analysis (PCA) and its role in dimensionality reduction
  • b
    What is clustering, and how does it differ from classification?
  • a
    Given stride S and kernel sizes for each layer of a (1-dimen sional) CNN, create a function to compute the receptive field of a part icular node in the network. This is just finding how many input nodes actually connect through to a neuron in a CNN
  • b
    Explain the concept of a kerne l function in machine learning. How does it enable Support Vector Machines (SVM) to perform classificati on in higher-dimensional spaces? Provide examples of three commonly u sed kernel functions and their applications
  • a
    Compare and contrast Bayesian estimation with Maximum Likeli hood Estimation (MLE). Highlight their advantages and disadvantages in the context of machine learning models
  • b
    Discuss the differences betwe en reinforcement learning and deep learning in the context of problem-solving

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 — KME074

Questions that appeared in more than one session, found by comparing 3 years of Machine Learning papers (2022-23, 2023-24, 2024-25)

2x

Differentiate between training data and testing data in machin e learning

Appeared in: 2022-23 · 2024-25

2x

Define hierarchical clustering

Appeared in: 2022-23 · 2024-25

Syllabus & More PYQs

Paper solve karne se pehle unit-wise syllabus dekh lo