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
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