GTU 3170924 AI and Machine Learning Summer 2026 Question Paper & PDF
- Total
- 70 marks
- To pass
- 23 marks (33%)
- Duration
- 2.5 Hours 2:30 PM – 5:00 PM
- Questions
- 5 with internal choice
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Q.2
14 MarksWhat is the significant of the activation function? Explain various activation functions used in feed forward NN.
Q.3
14 MarksDifferentiate simple linear regression method and multiple linear regression method used for prediction of output.
What are decision trees? Explain the meaning of decision node and leaf node.
Interpret collaborative filtering. Why it is used in recommender systems?
Q.4
14 MarksExplain the concept of hyperplanes, support vectors and the kernel trick in SVM.
Explain Logistic Regression approach in Machine Learning. Is Logistic Regression a Classification or Regression technique?
Find the crisp output Y1 and Y2 for the following membership functions using Centre of Area Defuzzification method. Assume X1=X2=4.
Brief various types of Membership Function used in fuzzy system and discuss any three MF in detail.
Q.5
14 MarksIs clustering approach supervised or unsupervised method of learning? Explain with the help of appropriate example.
With the help of a flowchart, explain the concept of Genetic Algorithm and importance of Mutation and Crossover for the same.
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Other Semester 7 subjects
BE Electrical
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About this paper
Official Gujarat Technological University (GTU) examination paper for AI and Machine Learning (Summer 2026, B.E. · Electrical Engineering, Sem 7). Features complete 70-mark regular & remedial examination pattern, official marking distribution across all 5 questions, and direct 1-click official PDF download.
Transcribed for student exam preparation from Gujarat Technological University official examination archives. Questions, syllabus guidelines, and curriculum marking schemes remain the intellectual property of Gujarat Technological University.