Machine Learning on R

About this Course

The program builds a solid foundation by covering the most popular and widely used machine learning technologies and its applications, including Naive Bayes theory and application, K Nearest Neighbors (KNN) theory and application, Random forest theory and application, Gradient Boosting Theory and Application and also Support Vector Machine Theory and Application–laying the building blocks for truly expanded analytical abilities.

What will you learn
  • Students will have a good working knowledge on Machine Learning on R and can use it for their Educational as well as Business projects and assignments.


Requirements

Prior knowledge of R programming and Data Science on R is recommended

Section

  • 7 Sections

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