This lecture delves into the kernel trick, a fundamental concept in machine learning, which allows algorithms to operate in a high-dimensional feature space without explicitly calculating the coordinates. The instructor explains how to augment features, compute the kernel function, and ensure the positive semi-definiteness of the kernel matrix.
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