svm

SVMs separate the candidates who memorized 'maximize the margin' from the ones who can explain why a kernel gives you non-linear separation without ever touching the high-dimensional space. Here is the answer that lands the second signal.

Most candidates can recite 'maximize the margin'. The dual is where you show you actually understand why only support vectors matter and where the kernel trick comes from. Here is the derivation an interviewer wants.