SVMs are supervised learning models that are used to build classifiers and regressors. An SVM finds the best separating boundary between the two sets of points by solving a system of mathematical equations. If you are not familiar with SVMs, here are a couple of good tutorials to get started:
Let's see how to build a linear classifier using an SVM.
Let's visualize our data to understand the problem at hand. We will use
svm.py that's already provided to you as a reference. Before we build the SVM, let's understand our data. We will use the