Deep Learning PYQ 2022-23 AKTU Question Paper

AKTU · BTECH · Semester 7 · Deep Learning · Session 2022-23 · PYQ

AKTU Deep Learning previous year question paper 2022-23 for B.Tech Semester 7. Covers Introduction to Neural Networks, Deep Networks, Dimensionality…

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Deep Learning AKTU syllabus

  1. Unit 1: Introduction to Neural Networks
  2. Unit 2: Deep Networks
  3. Unit 3: Dimensionality Reduction
  4. Unit 4: Optimization & Generalization
  5. Unit 5: Case Studies & Applications

Questions in Deep Learning AKTU PYQ 2022-23

  1. Q1a. What are the applications of Machine Learning? (2 marks, 2022-23)
  2. Q1b. Describe the Boltzmann Machine. (2 marks, 2022-23)
  3. Q1c. Is it possible to build deep learning models based solely on linear regression? Explain. (2 marks, 2022-23)
  4. Q1d. Define the different layers of a convolutional neural network. (2 marks, 2022-23)
  5. Q1e. Explain the linear models (2 marks, 2022-23)
  6. Q1f. Why is it important to introduce non-linearities in a neural network? (2 marks, 2022-23)
  7. Q1g. What are the limitations of using a perceptron? (2 marks, 2022-23)
  8. Q1h. Why do we use convolutions for images instead of using fully connected layers? (2 marks, 2022-23)
  9. Q1i. Why are GPUs important for implementing deep learning models? (2 marks, 2022-23)
  10. Q1j. Which is the best algorithm for face detection ? (2 marks, 2022-23)
  11. Q2a. Difference between Deep and Shallow Network. (10 marks, 2022-23)
  12. Q2b. Draw and explain the architecture of Convolutional Networks. (10 marks, 2022-23)
  13. Q2c. Why CNN is preferred over ANN for Image Classification tasks even though it is possible to solve image classification using ANN? (10 marks, 2022-23)
  14. Q2d. Explain LSTM (Long Short Term Memory ). Give some famous applications of LSTM. (10 marks, 2022-23)
  15. Q2e. Explain Image Captioning in Deep Learning. (10 marks, 2022-23)
  16. Q3a. Explain the difference between Gradient Descent and Stochastic Gradient Descent. (10 marks, 2022-23)
  17. Q3b. ExplainGAN and its models. Name and describe different types of GANs. (10 marks, 2022-23)
  18. Q4a. Examine the Semi –Supervised learning. (10 marks, 2022-23)
  19. Q4b. Demonstrate deep learning. Explain its uses, application and history. (10 marks, 2022-23)
  20. Q5a. Explain Back propagation with its algorithm. (10 marks, 2022-23)
  21. Q5b. Write short notes :- i) Deep Reinforcement ii) Autoencoder Architecture iii) VGG iv) SOA (10 marks, 2022-23)
  22. Q6a. Compare PCA (Principle Component Analysis ) and RNN. (10 marks, 2022-23)
  23. Q6b. Discuss how batch gradient descent and stochastic gradient descent are different. (10 marks, 2022-23)
  24. Q7a. Demonstrate how the privacy will be affected when facial recognition gets used by private companies? (10 marks, 2022-23)
  25. Q7b. How AI and Neuroscience drive each other forwards? Explain. (10 marks, 2022-23)

AKTU paper codes: BAI701, KCS078, KDS078, KOT076

Deep Learning previous year papers

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