Hefin Rhys

Training a Support Vector Machine in R with mlr Part Two

Learn to train, tune, and cross-validate an SVM model using R Studio and the MLR machine learning package.

Training a Support Vector Machine in R with mlr Part One

Hefin Rhys explains how the SVM algorithm works.

Exploring Machine learning with R and mlr

Exploring Machine learning with R and mlr features three chapters from Machine learning with R, tidyverse, and mlr by author and veteran research scientist Hefin I. Rhys. In the first chapter, you’ll get familiar with common machine learning terminology and different types of machine learning. Next, you’ll gain a solid foundation in the mlr package, R's machine learning answer to Python's scikit-learn. You’ll also drill down into more advanced machine learning theory while learning your first algorithm: k-nearest neighbors. In the final chapter, you’ll explore some of the most commonly used ML techniques including decision trees and ensembling, which can drastically improve the performance of an algorithm. This short but substantial guide is a great way to jumpstart your machine learning education.

Machine Learning with R, the tidyverse, and mlr

Machine Learning with R, the tidyverse, and mlr gets you started in machine learning using R Studio and the awesome mlr machine learning package. This practical guide simplifies theory and avoids needlessly complicated statistics or math. All core ML techniques are clearly explained through graphics and easy-to-grasp examples. In each engaging chapter, you’ll put a new algorithm into action to solve a quirky predictive analysis problem, including Titanic survival odds, spam email filtering, and poisoned wine investigation.