Machine Learning (KCA054) - AKTU Question Paper 2024-25
MCA · Semester 4 · Free PDF Download
This is the official AKTU Machine Learning Previous Year Question Paper for MCA Semester 4, academic session 2024-25. Published by Dr. A.P.J. Abdul Kalam Technical University (AKTU/UPTU), Lucknow. Free PDF download — no login required.
Course:MCA
Semester:Semester 4
Session:2024-25
University:AKTU / UPTU
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Questions Asked in 2024-25
Machine Learning (KCA054) — extracted question text · 100 marks · 3 Hours
Section AAttempt all questions in brief. 2 x 10 = 20
- bList out the four issues in Machine Learning
- cCan Logistic Regression be used for classification? Explain it
- dExplain the termhyperplane in SVM
- eIllustrate the issues in decision tree learning
- fExplain information gain
- gExplain unsupervised learning with an example
- hExplain Self Organizing Map (SOM). 4 K2 i. Describe reinforcement learning. 5 K1 j. Explain Markov Decision process
Section BAttempt any three of the following: 10 x 3 = 30
- aHow is the clustering approach different from decision tree learning?Point out the reasons
- bExplain the Naïve Bayes cla ssifier and its principle
- cExplain Instance-Based Learning. Compare Locally Weighted Regression and Radial Basis Function Networks
- dExplain the concept of perceptron along with its working wit h a suitable example
- eExplain in detail about Genetic Algorithm, its components an d its applications
Section CAttempt any one part of the following: 10 x 1 = 10
- aCompare between Machine Learning and Data Science. Mention o ne challenge faced in Machine Learning and explain why it's an issue
- bDescribe the architecture of an artificial neural network. S tate the learning parameters used in ANN
- aWhat is the importance of supp ort vector kernel? Explain its types
- bExpress your understanding of C oncept Learning. Also describ e in briefly the algorithms used for Concept Learning
- aDescribe ID-3 algorithm with an example
- bExplain k-Nearest Neighbor L earning algorithm with an example
- aExplain Types of Gradient Desc ent. Also explain Delta Rule a nd related algorithm
- bDescribe CNN architecture. Specify the function of each laye r
- aExplain Q-learning and D eep Q-learning in detail
- bAnalyze the components of Rei nforcement Learning along with its three different models
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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