mlr3 - A new framework for machine learning with R
Abstract: I'll give a short introduction to the 'mlr3' package (<https://mlr3.mlr-org.com>) for modern, state-of-the-art machine learning in R. The mlr3 ecosystem provides a one-stop solution for all machine learning (ML) needs, spanning preprocessing, model learning and evaluation, ensembles, visualization, and hyperparameter tuning. Its pipeline system 'mlr3pipelines' allows to easily express complex workflows, and to quickly prototype new ideas and applications. Whether you are applying ML to solve a practical prediction problem, implementing learning algorithms as a research software engineer or researching ML by empirical means, 'mlr3' can help make your workflow more readable and efficient.
Speaker: Dr. Michel Lang
- Graduation („Diplom“) in Statistics (TU Dortmund)
- Promotion at the “Collaborative Research Center SFB 876
- Providing Information by Resource-Constrained Data Analysis” (Computer Science/Statistics) in the context of project A3 ("Methods for Efficient Resource Utilization in Machine Learning Algorithms")
- Since 2019: Leader of Open Source and Open Data at the Munich Center for Machine Learning (MCML / Ludwig Maximilian University of Munich (LMU))
- Winter Term 19/20: Substitute Professorship Data Science at LMU