Question 1
(A figure from the original paper is missing from the source site.)
(A figure from the original paper is missing from the source site.)
(A figure from the original paper is missing from the source site.)
Question 2
Consider a vanilla Recurrent Neural Network (RNN) and an LSTM network with the same input dimension, hidden dimension, and output dimension.
Statement 1: The number of trainable parameters in a vanilla RNN is higher than that in an LSTM network. Statement 2: An LSTM has a higher number of parameters because it contains multiple gates (input gate, forget gate, output gate, and candidate state), each having separate weight matrices and biases.
Choose the correct option from the following.
Statement 1 is true, and Statement 2 is the correct reason.
Statement 1 is true, but Statement 2 is false.
Statement 1 is false, but Statement 2 is true.
Statement 1 is false, and Statement 2 is false.
Question 3
17 more questions in this paper
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More on the Deep Learning End Term 10 May 2026 paper
The IIT Madras BS Deep Learning (Deep Learning) End Term paper sat on 10 May 2026, in the January 2026 term: 20 questions for 50 marks in 180 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 End Term 10 May 2026 at a glance |
|---|---|
| Term | January 2026 term |
| Subject | Deep Learning |
| Course code | BSCS3004 |
| Questions | 20 |
| Marks | 50 |
| Duration | 180 min |
| MCQ | 6 |
| Numerical | 10 |
| MSQ | 4 |
| Official paper | Deep Learning 06 May 26 |
| Negative marking | No negative marking. |
| Updated |