Most classification algorithms find a boundary that separates classes. SVM finds the boundary that is as far away from both classes as possible. That extra distance is called the margin. And maximizing it is what makes SVM so good, especially when you don't have a lot of data. It sounds simple. The math underneath is not. But you don't need the math to use it well. You need to understand the ideas. What You'll Learn Here What a hyperplane and margin actually are What support ve...