Machine Learning (KME074) - AKTU Question Paper 2023-24
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 2023-24. 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:2023-24
University:AKTU / UPTU
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Questions Asked in 2023-24
Machine Learning (KME074) — extracted question text · 100 marks · 3 Hours
Section AAttempt all q u e s t i o n s i n b r i e f . 2 * 1 0 = 2 0
- aDefine Machine Learning and briefly explain its significanc e in today’s technological landscape
- bDifferentiate between Artif icial Intelligence (AI) and Machine Learning (ML), highlighting their key distinctions
- cWhat is the main difference between classification and regression analysis in supervised learning?
- dProvide a brief overview of the types of support vector ker nels
- eExplain the Multidimensional Scaling
- fHow does K-Means Clustering work in unsupervised learning?
- gDefine the Back propagation Algorithm in neural networks
- hOutline the basics of the Decision Tree algorithm. (i) Explain the meaning of reproduction in genetic algorithm (j) Explain the difference between reinforcement learning and d eep learning
Section BAttempt any three o f t h e f o l l o w i n g : 1 0 * 3 = 3 0
- aExplain the fundamental concepts of machine learning and di scuss its significance in various fields. Provide examples of real-world applications of machine learning in mechanical engineering
- bDiscuss the concept of bias and variance in the context of evaluating an estimator. How do these factors impact the performance of a machine learning model, and what strategies can be employed to strike a balance between them?
- cExplain the principles of unsupervised learning and delve i nto the workings of K-Means Clustering and the Expectation-Maximization Algorithm. Provide real-world examples where these techniques can be effectively applied
- dExplore the basics of Decision Trees, focusing on the ID3 A lgorithm and the role of information gain and entropy. Discuss the challenges associated with decision tree learning and potential solutions
- eDiscuss the Genetic algorithm (GA) with suitable example. A lso explain its advantages and applications
Section CAttempt any one p a r t o f t h e f o l l o w i n g : 1 0 * 1 = 1 0
- aDiscuss the key components involved in designing a machine learning system. Provide insights into the challenges and considerations during the design phase
- bDifferentiate between data science and machine learning. Discuss the overlap and unique aspects of these two fields
- aExplore the principles of Support Vector Machines (SVM). Di scuss the types of support vector kernels and the challenges associated with SVM. Provide a case study on car price prediction using SVM
- bWhat is regression in machine learning? Explain with exampl es
- aDraw the cluster of following 8 points into 3 clusters: A1= (10,7), A2=(8,6), A3=(9,4), A4=(5,8), A5=(7,5), A6=(7,4), A7=(3,2), A8=(4,9). Use the k-means algorithm and Euclidean distance and take the Initial cluster centers are A2(8, 6), A4(5, 8) & A8 (4,9). The solution up to two iterations
- bExplore Multidimensional Scaling and Linear Discriminant An alysis in the context of unsupervised learning. How do these methods contribute to data analysis and pattern recognition?
- aIntroduce neural networks, covering the perceptron and the Back propagation Algorithm. Explain the convergence analysis and the universal approximation theorem for the back propagation algorithm
- bExplore the concept of Convolutional Neural Networks (CNNs) and the different types of layers in CNN architecture. Provide a case study demonstrating the application of CNN in real-world scenarios such as self-driving cars or building a smart speaker
- aWhat is genetic algorithm? Explain with suitable example and give its advantages
- bExamine the principles of Reinforcement Learning and its ro le in training intelligent systems. Compare and contrast reinforcement learning with supervised and unsupervised learning. Provide examples of real-world scenarios where reinforcement le arning has been successfully applied
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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