Support Vector Machine Tutorial Using R | SVM Algorithm Explained | Data Science Training | Edureka
About this course
This course provides a comprehensive overview of Support Vector Machines (SVM), a powerful machine learning classifier. Participants will learn the fundamentals of machine learning, explore the workings of SVM, and discover how to classify both linearly and non-linearly separable data. The course includes practical applications, such as colon cancer classification and heart disease prediction, alongside a hands-on demo using R to build an SVM classifier from scratch.
What you should already know
Basic understanding of machine learning concepts and familiarity with R programming are required before taking the course.
What you will learn
By the end of the course, learners will be able to effectively implement SVM models for classification and regression tasks, evaluate their performance, and understand the underlying principles of how SVM operates.