Support Vector Machine (SVM) is a supervised machine learning algorithm that can be used for classification as well as regression challenges. It is said to be one of the most popular high-performance algorithms and is implemented in practice using a kernel. In this algorithm, the dataset explains SVM about classes so that it can classify new data. It works by classifying data through finding the line which separates data into classes. It tries to maximise the distance between the various classes and referred as margin maximisation.