Support vector machines (SVMs) are a particularly powerful and flexible class of supervised algorithms for both classification and regression. SVMs were introduced initially in the 1960s and were later refined in 1990s. However, it is only now that they are becoming extremely popular, owing to their ability to achieve brilliant results. SVMs are implemented uniquely when compared to other machine learning algorithms.
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