Answer / Vishal Rastogi

The “kernel trick” is a method used in support vector machines (SVM) to transform data from an original space into a higher dimensional space, making it possible to separate or classify complex data sets that may not be linearly separable in the original space. By using a kernel function, SVMs can operate in spaces of any dimension, without explicitly computing the coordinates of the transformed data. This is useful for solving complex classification and regression problems.

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