Deep Learning (KDS078) - AKTU Question Paper 2024-25
B.Tech · Semester 7 · Free PDF Download
This is the official AKTU Deep Learning Previous Year Question Paper for B.Tech Semester 7, academic session 2024-25. Published by Dr. A.P.J. Abdul Kalam Technical University (AKTU/UPTU), Lucknow. Free PDF download — no login required.
Course:B.Tech
Semester:Semester 7
Session:2024-25
University:AKTU / UPTU
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Questions Asked in 2024-25
Deep Learning (KDS078) — complete question paper · 100 marks · 3 Hours
Section AAttempt allquestionsinbrief. 2x10=20
- aDiscuss the differences between a perceptron and a support vector machine in terms of learning
- bDefine and explain the role of a loss function in neural networks
- cDiscuss the role of convolutional layers in Convolutional Neural Networks
- dCompare deep and shallow networks in terms of representational capacity and computational complexity
- eDiscuss how batch normalization impacts the training of convolutional neural networks
- fHow autoencoders can be used to learn low-dimensional representations of data?
- gDiscuss the role of non-convex optimization in deep learning
- hAnalyze the challenges of stochastic optimization in deep learning. 4 K3 i. How deep learning models have revolutionized computer vision tasks? 5 K3 j. What are the key challenges in modeling audio signals?
Section B
- 2Attemptany threeofthefollowing: 10x3=20 Question C Level
- aExplain the mathematical foundation of the Support Vector Machine (SVM) algorithm and describe its kernel trick for non-linear classification problems. How does it differ from logistic regression?
- bDerive and explain the role of batch normalization in accelerating deep neural network training. How does it help in reducing internal covariate shifts?
- cDescribe the process of hyperparameter optimization in training a ConvNet. What are the key hyperparameters, and how do they influence network performance?
- dCompare and contrast LSTMs and traditional recurrent neural networks (RNNs). How do LSTMs mitigate the vanishing gradient problem in sequence modeling?
- eAnalyze the applications of deep learning in bioinformatics. Provide examples of how neural networks are used for tasks like protein structure prediction
Section C
- 3Attemptany onepartofthefollowing: 10x1=10 Question C Level
- aExplain the concept of stochastic gradient descent (SGD). How does it differ from batch and mini-batch gradient descent in terms of computational PrintedPage:2of2 SubjectCode:KDS078 (SEMVII)THEORYEXAMINATION2024-25 DEEPLEARNING efficiency and convergence?
- bCompare and contrast the theoretical underpinnings of perceptrons and logistic regression in the context of binary classification problems
- 4Attemptany onepartofthefollowing: 10x1=10 Question C Level
- aExplain the architecture and training process of a Generative Adversarial Network. What challenges arise during training, and how can they be mitigated?
- bDiscuss the probabilistic theory behind deep learning models. How do Bayesian principles apply to the optimization and uncertainty estimation in deep networks?
- 5Attemptany onepartofthefollowing: 10x1=10 Question CO Leve
- aCompare Principal Component Analysis and Linear Discriminant Analysis terms of their objectives and mathematical formulations. Provide examples of their use in classification tasks
- bDerive the reconstruction loss of an autoencoder. How does this loss relate to the dimensionality reduction capabilities of the network?
- 6Attemptany onepartofthefollowing: 10x1=10 Question CO Leve
- aExplain how deep reinforcement learning combines reinforcement learning principles with deep network architectures
- bDerive the architecture of a recurrent neural network language model. Discuss its strengths and limitations compared to word-level RNNs
- 7Attemptany onepartofthefollowing: 10x1=10 Question CO Leve
- aDiscuss the limitations of deep learning models in real-world applications. How can interpretability and ethical considerations be integrated into these systems?
- bExplain the architecture of a deep learning model used for face recognition. How does it ensure robustness against variations in pose and illumination?
Question text is extracted from the official AKTU question paper PDF above. Hindi translations are omitted — every question is printed in English in the original paper. Last verified: 2026-08-23.
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