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Explore Support Vector Machines (SVM), a powerful supervised learning algorithm for classification and regression. Learn how SVM works, including hyperplanes, support vectors, and margins. Discover different SVM types like linear and non-linear, and understand kernel functions (Linear, Polynomial, RBF, Sigmoid).
Support Vector Machines (SVM) is a powerful supervised machine learning algorithm for classification and regression tasks. It finds a hyperplane that separates data points belonging to different classes, making it effective for complex problems.
In this article, you will learn about Support Vector Machine.
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