Your question is L1 vs L2 Regularization. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
Explain the mathematical difference between L1 and L2 regularization, and describe scenarios where you would prefer one over the other.
Keep your answer focused on the penalty terms, their effect on coefficients, and the practical tradeoffs in model training. You may mention sparsity, feature selection, and robustness to correlated features.