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 will have an important hands-on component and participants will need to bring a computer with R 3.4.1 pre-installed. All the course material will be made available online and package instructions will be circulated in advance.
Required audience experience: Basic R knowledge.
Objective of the training: Get hands-on experience of typical machine learning applications in R.
Keywords: Machine Learning, R, clustering, classification, regression, k-means, k-nearest neighbour, pca, principal component analysis