Q.1
14 Marks(a)
List out the key components found in a neural network.
(c)
What is overfitting? Expalin any three methods to prevent overfitting in neural networks.
Gujarat Technological UniversitySummer 2025 examination
GTU 116AG01 Deep Learning and Neural Network Summer 2025 Question Paper & PDF
B.E. · Computer Engineering · Semester 6 · Subject code 116AG01
- Total
- 70 marks
- To pass
- 23 marks (33%)
- Duration
- 2.5 Hours 10:30 AM – 1:00 PM
- Questions
- 5 with internal choice
No solutions on this paper yetNeed them for your exam? Ask once. Papers that students ask for are solved first, and we aim to add them within 24 hours.
Noted. This paper is in our queue now. Check back tomorrow.
We could not record that here. Email the paper name to hirenjsca@gmail.com and we will add it.
11 of 25 questions on this paper were also asked in other years. Each is marked below with the years it appeared.See all 14 repeated 116AG01 questions, most asked first
Q.2
14 Marks(c)
List and explain the various activation functions used in modeling of neural network.
Also asked in Summer 2026 Q2c, Summer 2024 Q1c
OR
(c)
Explain Back propagation with its algorithm in Artificial Neural Network.
Q.3
14 Marks(b)
What are different loss functions and their use case?
OR
(a)
Calculate the output of the following neuron Y with the activation function as a sigmoid activation function.
(b)
Compare Single layer perceptron and Multi layer perceptron.
Q.4
14 Marks(a)
Explain optimizers. Why optimizers are required?
(b)
Explain effect of learning rate in convergence of a neural network during training.
(c)
Draw and explain the architecture of Convolutional Neural Networks.
Also asked in Summer 2026 Q3c, Winter 2025 Q3b, Summer 2024 Q3c OR
OR
(a)
Write applications of Deep Learning.
(b)
Explain the role of pooling layer in CNN. Find Feature map after applying Maxpool 2 x 2 with stride=1 on the following feature map. 12 1 5 1 6 9 0 0 7 5 1 8 0 3 6
(c)
Suppose 10000 patients get tested for flu; out of them 9000 are actually healthy and 1000 are actually sick. For the sick people, a test was positive for 620 and negative for 380. For healthy people, the same test was positive for 180 and negative for 8820. Construct a confusion matrix for the data and compute the accuracy, precision and recall for the data.
Q.5
14 Marks(a)
Explain TensorFlow components.
(b)
Write the differences between eager execution and graph execution modes in TensorFlow.
OR
(a)
Write steps to train neural network model.
More Deep Learning and Neural Network papers
Questions repeat across sessions. Working through two or three papers shows you which topics GTU asks most.
Other Semester 6 subjects
BE Computer
Preparing with friends?
Send this paper to your class group. Every question has its own link.
About this paper
Official Gujarat Technological University (GTU) examination paper for Deep Learning and Neural Network (Summer 2025, B.E. · Computer Engineering, Sem 6). 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.