IG Machine Learning

Short description
The IG 'Machine Learning' (ML@NFDI4Earth) within the framework of NFDI4Earth addresses the growing digital needs of the individual disciplines and sub-disciplines within all addressed Earth system sciences (ESS). The aim of ML@NFDI4Earth is to maximize synergies and bundle information about ML activities in the field of ESS and to improve exchange between stakeholders across disciplinary boundaries.

Summary, i.e. ML@NFDI4EARTH Topics
The network will gather and identify projects in the area of ML@NFDI4Earth, research topics, used techniques, best practices, software, frameworks, benchmarks, data sets, hardware setups, etc. 

Concrete questions are:
- How are ML frameworks installed at RDIs? 
- How to interface common ML frameworks with data stored in the ESS? 
- Have training, validation, test and verification data sets enough meta data?
- Do data management plans consider ML data sets already? 
- Scalability of approaches from laptop to HPC? 
- Are the interfaces available to fully exploit new ML in rather old Earth system modeling and analysis frameworks? (e.g. python / fortran / Julia interfaces)

Illustrating material & further links

Machine Learning at NFDI4Earth (slides of 1st Plenary Meeting 2022)

Mailing list to subsrice

Current agenda and next meetings resp.
17 May 2023, 15:00 hrs

Christopher Kadow - DKRZ, Hamburg
Christopher Irrgang - RKI, Berlin

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