Question 2
Which of the following is true about the singular value decomposition (SVD)?
Question 3
In the context of Principal Component Analysis (PCA), which of the following statements is/are correct?
PCA projects the original data onto a lower-dimensional subspace that captures the maximum variance.
The eigenvectors of the covariance matrix correspond to the directions of maximum variance.
The principal components form a basis that is not necessarily orthogonal.
The principal components obtained through PCA are always uncorrelated.
11 more questions in this paper
Sign in with Google — it is free — to see every question with its answer and explanation, practise it in learning mode, or take it as a timed mock test.
More on the MLF End Term 13 Apr 2025 Set QDD1 paper
The IIT Madras BS Machine Learning Foundations (MLF) End Term paper sat on 13 Apr 2025, in the January 2025 term, set QDD1: 14 questions for 40 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 | MLF End Term 13 Apr 2025 Set QDD1 at a glance |
|---|---|
| Term | January 2025 term |
| Subject | Machine Learning Foundations |
| Course code | BSCS2004 |
| Questions | 14 |
| Marks | 40 |
| Duration | 180 min |
| MCQ | 1 |
| MSQ | 8 |
| Numerical | 5 |
| Official paper | IIT M DIPLOMA AN EXAM QDD3 13 Apr 2025 |
| Negative marking | No negative marking. |
| Updated |