Support Vector Machine, Svm, Kernel Trick, Margin.
In cases where the data isn’t linearly separable, SVMs might struggle to find an optimal linear boundary. Here’s where the kernel trick comes into play — a technique that lifts the data into a higher-dimensional space where it might become linearly separable. Rather than directly transforming the