Introduction to Machine Learning with R and mlr3

DAGStat 2025, Berlin

Bernd Bischl, Marvin N. Wright

Schedule

Morning Session 1

• Theory: Machine Learning Basics Slides (pdf)
• Hands-On Intro: Introduction to mlr3 Slides (html)
• Hands-On Practical: Train/Predict/Evaluate Exercise (html) Solution (html)

Morning Session 2

• Theory: Resampling and Benchmarking Slides (pdf)
• Hands-On Intro: Introduction to mlr3 (cont.) Slides (html)
• Hands-On Practical 1: Resampling Exercise (html) Solution (html)
• Hands-On Practical 2: Benchmarking Exercise (html) Solution (html)

Afternoon Session 1

• Theory: Tuning and Nested Resampling Slides (pdf)
• Hands-On Intro: Introduction to mlr3 (cont.) Slides (html)
• Hands-On Practical: Hyperparameter Tuning Exercise (html) Solution (html)

Afternoon Session 2

• Hands-On Intro: Introduction to mlr3 (cont.) Slides (html)
• Hands-On Practical 1: Feature Encoding Exercise (html) Solution (html)
• Hands-On Practical 2: Advanced Pipelines Exercise (html) Solution (html)