Machine Learning with R at LRZ

The programming language R offers a large amount of add-on packages that implement ideas and methods from the field of machine learning.

The mlr package (Machine Learning in R) provides a unified interface to many of these algorithms. It allows to utilize supervised methods like classification, regression and survival analyses along with their corresponding optimization and evaluation methods, as well unsupervised methods like clustering. This includes a consistent infrastructure for common data pre- and post-processing steps, feature selection, hyperparameter optimization, resampling and model comparison.

In this workshop, we will provide an introduction to the mlr package (as well as its successor mlr3) and demonstrate how it can be used to deploy highly parallelized machine learning tasks on LRZ high performance computing systems. Participants will be able to work on instructor-led excercises and hands-on examples. There will be breaks during the session.

Basic knowledge of R

Certificates of attendance for

• Introduction to GNU/Linux and the Shell (or comparable previous knowledge)
• Introduction to Working on Remote Systems with SSH (or comparable previous knowledge)
• Introduction to the LRZ HPC Infrastructure (or comparable previous knowledge)
• Using R at LRZ (or comparable previous knowledge)

All participants are expected to bring their own laptops.

Essential Data Science Training (https://www.essentialds.de/)

J. Albert-von der Gönna (LRZ)

Slides

Demos/Excercises