This repository provides a short introduction into the most popular model-agnostic IML (interpretable machine learning) methods. The theoretical background and examples are demonstrated via a slide set. Users can apply this knowledge on various excercises on real-world data, which are also provided with detailed solutions.
-
Notifications
You must be signed in to change notification settings - Fork 1
This repository provides a short introduction into the most popular model-agnostic IML (interpretable machine learning) methods. A presentation containing the theoretical background and examples as well as excercises on real-world data are included.
License
slds-lmu/introduction_iml_bliz_summerschool
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Folders and files
Name | Name | Last commit message | Last commit date | |
---|---|---|---|---|
Repository files navigation
About
This repository provides a short introduction into the most popular model-agnostic IML (interpretable machine learning) methods. A presentation containing the theoretical background and examples as well as excercises on real-world data are included.
Resources
License
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published