SVM Classifier and RBF Kernel -- How to Make Better Models in Python

It is essential to understand how different Machine Learning algorithms work to succeed in your Data Science projects. I have written this story as part of the series that dives into each ML algorithm explaining its mechanics, supplemented by Python code examples and intuitive visualizations. Support Vector Machines (SVMs) are most frequently used for solving classification problems, which fall under the supervised machine learning category. The exact place of these algorithms is displayed in the diagram below. Let's assume we have a set of points that belong to two separate classes.