Question 1
Consider the following code:
It enables gradient computation
It resets the model parameters every epoch
It clears previously stored gradients
It ensures layers like Dropout and BatchNorm behave correctly during training
Consider the following code:
It enables gradient computation
It resets the model parameters every epoch
It clears previously stored gradients
It ensures layers like Dropout and BatchNorm behave correctly during training
Consider the following code:
What is the spatial size of the output after applying the given pooling code?
2x3
2x2
1x1
1x2
Which of the following code snippets generates fake images from random noise for training a fully connected GAN network?
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The IIT Madras BS Introduction to Deep Learning and Generative AI (Deep Learning and GenAI) Quiz 2 paper sat on 12 Apr 2026, in the January 2026 term: 20 questions for 48 marks in 120 minutes. The first 3 questions are below. Sign in with Google — it is free — to see the whole paper with its answers and explanations, in learning mode or as a timed mock test.
| Feature | Deep Learning and GenAI Quiz 2 12 Apr 2026 at a glance |
|---|---|
| Term | January 2026 term |
| Subject | Introduction to Deep Learning and Generative AI |
| Course code | BSDA2001 |
| Questions | 20 |
| Marks | 48 |
| Duration | 120 min |
| MCQ | 15 |
| Numerical | 1 |
| MSQ | 4 |
| Official paper | Introduction To Deep Learning And Generative Ai 06 Apr 26 |
| Negative marking | No negative marking. |
| Updated |