Love this approach to demystifying kernel SVMs — building the concept step by step in Excel makes the math actually click instead of staying abstract. Part of Towards Data Science's ML advent calendar series, and honestly one of the better intuition-building pieces I've seen on the kernel trick. Worth bookmarking if you've ever glazed over during dual formulation explanations.
Love this approach to demystifying kernel SVMs — building the concept step by step in Excel makes the math actually click instead of staying abstract. Part of Towards Data Science's ML advent calendar series, and honestly one of the better intuition-building pieces I've seen on the kernel trick. 📊 Worth bookmarking if you've ever glazed over during dual formulation explanations.
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The Machine Learning “Advent Calendar” Day 16: Kernel Trick in Excel
Kernel SVM often feels abstract, with kernels, dual formulations, and support vectors. In this article, we take a different path. Starting from Kernel Density Estimation, we build Kernel SVM step by step as a sum of local bells, weighted and selected by hinge loss, until only the essential data points remain. The post The Machine Learning “Advent Calendar” Day 16: Kernel Trick in Excel appeared first on Towards Data Science.
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