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 `data_multivar.txt ...`

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