# Course Support Vector Machines in R

This course will introduce the support vector machine (SVM) using an intuitive, visual approach.

**Description**

**Chapters**

**Exercises**

**Instructor**

This **online course** about Support Vector Machines in R covers a key part of what a future data analyst would require.

This course will introduce a powerful classifier, the support vector machine (SVM) using an intuitive, visual approach. Support Vector Machines in R will help students develop an understanding of the SVM model as a classifier and gain practical experience using R’s libsvm implementation from the e1071 package. Along the way, students will gain an intuitive understanding of important concepts, such as hard and soft margins, the kernel trick, different types of kernels, and how to tune SVM parameters. Get ready to classify data with this impressive model.

Enroll now in this *Support Vector Machines in R course*, and don’t miss the opportunity of learning with the best, as Kailash Awati is. With 47 enriching exercises, 13 videos, and an estimated time of 4 hours to successfully end up the course, you will become one of the best.

**Kailash Awati**

*Senior Lecturer at University of Technology Sydney.*

Kailash Awati is co-founder and principal of Sensanalytics, a consultancy specializing in sensemaking and analytics. He is also on the academic staff at the University of Technology Sydney where he teaches into the Master of Data Science and Innovation program. He blogs about analytics, sensemaking and his other professional interests at Eight to Late.