Skip to content

ScPoEcon/IntroMachineLearningWithR

 
 

Repository files navigation

An Introduction to Machine Learning with R

This introductory workshop on machine learning with R is aimed at participants who are not experts in machine learning (introductory material will be presented as part of the course), but have some familiarity with scripting in general and R in particular. The workshop will offer a hands-on overview of typical machine learning applications in R, including unsupervised (clustering, such as hierarchical and k-means clustering, and dimensionality reduction, such as principal component analysis) and supervised (classification and regression, such as K-nearest neighbour and linear regression) methods. We will also address questions such as model selection using cross-validation. The material has an important hands-on component and readers should have a computer running R 3.4.1 or later.

Read the latest version of the the course at http://bit.ly/intromlr

Taught on

License

This material is licensed under the Creative Commons Attribution-ShareAlike 3.0 License. Some content is inspired by other sources though, see the Credit section in the material.

About

An Introduction to Machine Learning with R

Resources

Stars

Watchers

Forks

Packages

No packages published

Languages

  • R 74.7%
  • TeX 24.8%
  • Makefile 0.5%