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EndsemMay 20252019 patternTE IT

Artificial Intelligence & Machine Learning (AIML) SPPU Endsem Question Paper May 2025

All 8 questions from this SPPU endsem paper, as printed. Read them here or open the PDF.

Open the PDFMost repeated AIML questions
Subject code
314443
Pattern
2019 pattern
Exam
Endsem
Session
May 2025
Max. marks
70
Time
2½ Hours
Semester
V
Paper code
[6403]-122

Printed for: T.E. (I.T)

Instructions to the candidates

  1. Answer Q1 or Q2, Q3 or Q4, Q5 or Q6, Q7 or Q8.
  2. Neat diagrams must be drawn wherever necessary.
  3. Figures to the right side indicate full marks.
  4. Assume Suitable data if necessary.

Questions

  1. Q1

    1. a)

      Define Regression and explain types of regression with proper examples.

      [6]
    2. b)

      Explain Generalization Issues with Overfitting, Underfitting and Bias, Variance.

      [5]
    3. c)

      Explain Least-Square Method for finding values of the regression coefficients

      [6]

  2. Q2

    1. a)

      Explain Simple Linear Regression with Gradient Descent Algorithm.

      [6]
    2. b)

      Explain Multivariate Regression with model representation.

      [5]
    3. c)

      Write short note on Vapnik-Chervonenkis dimension.

      [6]

  3. Q3

    1. a)

      What is Decision Tree? Explain Concepts and Terminologies.

      [8]
    2. b)

      Explain Bayes Rule & Naive Bayes Classifier.

      [4]
    3. c)

      Define Gini Index, Information gain and Entropy.

      [6]

  4. Q4

    1. a)

      Explain feature tree & comment on best split algorithm.

      [12]
    2. b)

      Explain Conditional Probability, Joint Probability and Probability Density Function.

      [6]

  5. Q5

    1. a)

      Apply Apriori algorithm for following set of transactions and find all the association rules with min support = 1 and min confidence = 60%. Transaction ID Transactions 1 1,3,4 2 2,3,5 3 1,2,3,5 4 2,5

      [12]
    2. b)

      Define and explain various Distance Metrics.

      [6]

  6. Q6

    1. a)

      This part has equations that don’t show as text. Open the PDF to read it.

      [10]
    2. b)

      What is distance metric? Explain any three distance measures.

      [8]

  7. Q7

    1. a)

      Explain different Activation Functions and it’s types.

      [6]
    2. b)

      Explain Multi-layer Perceptron with example.

      [6]
    3. c)

      Write a note on Loss function- Mean Square Error.

      Also asked:Nov 2025

      [5]

  8. Q8

    1. a)

      Explain Perceptron with it’s Learning Aigorithm.

      [6]
    2. b)

      Write a note on ANN.

      [6]
    3. c)

      Elaborate Deep Learning in detail. 

      [5]