MLAir (v1.0.0) - a tool to enable fast and flexible machine learning on air data time series - Source Code

MLAir (Machine Learning on Air data) is an environment that simplifies and accelerates the creation of new machine learning (ML) models for the analysis and forecasting of meteorological and air quality time series.

Current developments can be tracked in the gitlab repository: https://gitlab.version.fz-juelich.de/toar/mlair

This resource contains the MLAir version 1.0.0 in a zip archive, as well the requirements, a readme, and distribution file for easy installation using the package installer for python (pip). Instructions on the installation von MLAir can be found in the readme file.

Identifier
DOI https://doi.org/10.34730/fcc6b509d5394dad8cfdfc6e9fff2bec
PID http://hdl.handle.net/21.11125/a85fa50d-e716-459b-9339-460be9d5c475
Source https://b2share.fz-juelich.de/api/records/fcc6b509d5394dad8cfdfc6e9fff2bec
Metadata Access https://b2share.fz-juelich.de/api/oai2d?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai:b2share.fz-juelich.de:b2rec/fcc6b509d5394dad8cfdfc6e9fff2bec
Provenance
Creator Leufen, Lukas Hubert; Kleinert, Felix; Schultz, Martin Georg
Publisher B2SHARE FZJ
Publication Year 2020
Rights info:eu-repo/semantics/openAccess; The MIT License (MIT)
OpenAccess true
Representation
Language English
Resource Type Software
Discipline Various