Question 2
Question 3
Linear regression without regularization will achieve training MSE less than or equal to that of ridge regression.
The solution for linear regression without regularization may not be unique.
Ridge regression (L2 regularization) will always set at least one coefficient exactly to zero.
Lasso regression (L1 regularization) can force some feature weights to become exactly zero.
13 more questions in this paper
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More on the MLT End Term 10 May 2026 Set 1 paper
The IIT Madras BS Machine Learning Techniques (MLT) End Term paper sat on 10 May 2026, in the January 2026 term, set 1: 16 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 | MLT End Term 10 May 2026 Set 1 at a glance |
|---|---|
| Term | January 2026 term |
| Subject | Machine Learning Techniques |
| Course code | BSCS2007 |
| Questions | 16 |
| Marks | 50 |
| Duration | 180 min |
| MCQ | 6 |
| MSQ | 4 |
| Numerical | 6 |
| Official paper | Machine Learning Techniques 06 May 26 |
| Negative marking | No negative marking. |
| Updated |