Summary

In this chapter, you learned about how Support Vector Machines help in classification problems. You learned about the formula for finding the hyperplane, as well as the two accompanying margins. Fortunately, Scikit‐learn provides the classes needed for training models using SVM, and with the parameters returned, you can plot the hyperplane and margins visually so that you can understand how SVM works. You also learned about the various kernels that you can apply to your SVM algorithms so that the dataset can be separated linearly.