Description
We are currently starting to devise a course entitled "A practical guide to dimension reduction and feature selection". The idea is to showcase dimensionality reduction methods, feature selection and stability analysis not on toy data but on a real-world high-dimensional dataset. We already selected a gene expression dataset as an example to discuss advantages of and issues with dimension reduction approaches. During the retreat, we would like to invite our fellow consultants to comment on the planned content, test and extend some preliminary jupyter notebooks, or add methods explanations and further contributions. All kind of input is welcome, no matter whether it is hands-on, theoretical, or conceptual, and whether you have expertise in the topic or approach it from a learner's perspective.
