Machine Learning Techniques PYQ 2020-21 AKTU (KCS055)

AKTU · BTECH · Semester 5, 6 · Machine Learning Techniques · Session 2020-21 · PYQ

AKTU Machine Learning Techniques (KCS055) previous year question paper 2020-21 for B.Tech Semester 5/6. Covers Introduction, Regression, Bayesian Learning…

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Machine Learning Techniques AKTU syllabus

  1. Unit 1: Introduction
  2. Unit 2: Regression, Bayesian Learning and Support Vector Machine
  3. Unit 3: Decision Tree Learning and Instance-Based Learning
  4. Unit 4: Artificial Neural Networks and Deep Learning
  5. Unit 5: Reinforcement Learning and Genetic Algorithms

Questions in Machine Learning Techniques AKTU PYQ 2020-21

  1. Q1a. Explain the concept of machine learning. (2 marks, 2020-21)
  2. Q1b. Compare ANN and Bayesian networks. (2 marks, 2020-21)
  3. Q1c. What is the difference between linear and logistic regression? (2 marks, 2020-21)
  4. Q1d. Discuss support vectors in SVM? (2 marks, 2020-21)
  5. Q1e. Discuss overfitting and underfitting situation in decision tree learning. (2 marks, 2020-21)
  6. Q1f. What is the task of the E-step of the EM-algorithm? (2 marks, 2020-21)
  7. Q1g. Define the learning classifiers. (2 marks, 2020-21)
  8. Q1h. What is the difference between machine learning and deep learning? (2 marks, 2020-21)
  9. Q1i. What objective function do regression trees minimize? (2 marks, 2020-21)
  10. Q1j. What is the difference between Q learning and deep Q learning? (2 marks, 2020-21)
  11. Q2a. Apply KNN for following dataset and predict class of test example (A1=3, A2=7).Assume K=3 (10 marks, 2020-21)
  12. Q2b. Describe the Kohonen Self-Organizing Maps and its algorithm. (10 marks, 2020-21)
  13. Q2c. Explain the various learning models for reinforcement learning. (10 marks, 2020-21)
  14. Q2d. Explain the role of genetic algorithm? Discuss the various phases considered in genetic algorithm. (10 marks, 2020-21)
  15. Q2e. Describe BPN algorithm in ANN along with a suitable example. (10 marks, 2020-21)
  16. Q3a. Why SVM is an example of a large margin classifier? Discuss the different kernels functions used in SVM. (10 marks, 2020-21)
  17. Q3b. Explain the relevance of CBR. How CADET tool employs CBR? (10 marks, 2020-21)
  18. Q4a. Discuss the applications, properties, issues, and disadvantages of SVM. (10 marks, 2020-21)
  19. Q4b. Explain the Confusion Matrix with respect to Machine Learning Algorithms. (10 marks, 2020-21)
  20. Q5a. Illustrate the operation of the ID3 training example. Consider information gain as attribute measure. (10 marks, 2020-21)
  21. Q5b. Describe Markov Decision Process in reinforcement learning. (10 marks, 2020-21)
  22. Q6a. What is instance based learning? How Locally Weighted Regression is different from Radial basis function networks? (10 marks, 2020-21)
  23. Q6b. How is Bayes theorem used in machine learning? How naive Bayes algorithm is different from Bayes theorem? (10 marks, 2020-21)
  24. Q7a. Compare regression, classification and clustering in machine learning along with suitable real life applications? (10 marks, 2020-21)
  25. Q7b. Given below is an input matrix named I, kernel matrix, calculate the Convoluted matrix C using stride =1 also apply max pooling on C. (10 marks, 2020-21)

AKTU paper codes: BCS055, KCS055, BCDS062, KAI601

Machine Learning Techniques previous year papers

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