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
Contact/s
Christopher Kadow - DKRZ, Hamburg
Christopher Irrgang - RKI, Berlin