What is a co-occurrence matrix in the context of Natural Language Processing?
A matrix representing similarity scores between documents
A matrix where rows and columns represent words, and each cell indicates how frequently two words appear together in a context
A matrix that stores only the most frequent word in each document
A neural network used to compute word embeddings directly
What is the primary advantage of word embeddings compared to one-hot encoding?
Simpler implementation
Captures semantic relationships
They automatically correct spelling errors
Word embeddings are sparser than one-hot encoding
Which of the following is not true about multi-head cross attention?
Keys and values are taken from the encoder outputs
Queries come from the decoder outputs
All heads attend to identical features due to shared projection matrices
Each head learns to attend to different representation subspaces
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The IIT Madras BS Deep Learning (Deep Learning) End Term paper sat on 21 Dec 2025, in the September 2025 term: 32 questions for 79 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 21 Dec 2025 at a glance |
|---|---|
| Term | September 2025 term |
| Subject | Deep Learning |
| Course code | BSCS3004 |
| Questions | 32 |
| Marks | 79 |
| Duration | 180 min |
| MCQ | 10 |
| MSQ | 6 |
| Numerical | 16 |
| Official paper | Deep Learning 18 Dec 25 |
| Negative marking | No negative marking. |
| Updated |
