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EndsemMay 20242019 patternBE Comp

Deep Learning (DL) SPPU Endsem Question Paper May 2024

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

Open the PDFMost repeated DL questions
Subject code
410251
Pattern
2019 pattern
Exam
Endsem
Session
May 2024
Max. marks
70
Time
2½ Hours
Semester
VIII
Paper code
[6263]-95

Printed for: B.E. (Computer Engineering)

Instructions to the candidates

  1. Solve Q.1 or Q.2, Q.3 or Q.4, Q.5 or Q.6, Q.7 or Q.8.
  2. Figures to the right indicate full marks.
  3. Neat diagrams must be drawn whenever necessary.
  4. Make suitable assumption whenever necessary.

Questions

  1. Q1

    1. a)

      Explain CNN architecture with its application.

      [6]
    2. b)

      What is Padding? Enlist and explain types of padding.

      [6]
    3. c)

      Explain Dropout Layer in Convolutional Neural Network.

      Also asked:May 2023

      [6]

  2. Q2

    1. a)

      Define ReLU. Explain disadvantages of ReLU.

      [6]
    2. b)

      What is Strides in CNN? Explain in brief.

      [6]
    3. c)

      Explain Pooling Layer with its different types.

      Also asked:May 2025 ·Nov 2023 ·May 2023

      [6]

  3. Q3

    1. a)

      Explain RNN with its types.

      [6]
    2. b)

      Explain in brief Encoder Decoder architecture.

      Also asked:May 2023

      [6]
    3. c)

      Explain Different types of Deep Learning.

      [5]

  4. Q4

    1. a)

      WSN on Performance Matrices.

      [6]
    2. b)

      Compare implicit and explicit memory.

      [6]
    3. c)

      What are default baseline models? Explain in brief.

      [5]

  5. Q5

    1. a)

      State and explain different types of GAN.

      Also asked:Nov 2023

      [6]
    2. b)

      What is Boltzmann machine? Explain its objectives.

      [6]
    3. c)

      Write short Note on Deep generative model and Deep Belief Networks. 2

      Also asked:Nov 2025 ·May 2025 ·Nov 2023 ·May 2023

      [6]

  6. Q6

    1. a)

      Define Boltzmann machine? State and Explain its types.

      [6]
    2. b)

      Explain Discriminator network.

      [6]
    3. c)

      Enlist and Explain applications of GAN.

      [6]

  7. Q7

    1. a)

      What is Reinforcement Learning? State and explain its advantages and disadvantages.

      [6]
    2. b)

      What are different types of Reinforcement Learning? Explain in brief.

      [6]
    3. c)

      Compare Active and Passive Reinforcement Learning.

      [5]

  8. Q8

    1. a)

      Write short note on Deep Q-Learning.

      [6]
    2. b)

      What are different characteristics of Reinforcement Learning?

      [6]
    3. c)

      Explain in detail Dynamic programming algorithms for reinforcement learning.   

      Also asked:Nov 2024 ·Nov 2023 ·May 2023

      [5]