UK RSE Conference 2022 Walkthrough - MLOps for RSEs - Sample Data
This record is intended as sample data for a Walkthrough at the UK RSE 2022 Conference titled "MLOps for RSEs". The code that uses this sample dataset can be found on GitHub. There are 2 parts based on the sample problems in the walkthrough Classifying wind rotor events Clustering weather...
Main Author: | |
---|---|
Format: | Dataset |
Language: | English |
Published: |
2022
|
Subjects: | |
Online Access: | https://zenodo.org/record/7022648 https://doi.org/10.5281/zenodo.7022648 |
id |
ftzenodo:oai:zenodo.org:7022648 |
---|---|
record_format |
openpolar |
spelling |
ftzenodo:oai:zenodo.org:7022648 2023-05-15T17:34:17+02:00 UK RSE Conference 2022 Walkthrough - MLOps for RSEs - Sample Data Stephen Hadadad 2022-08-05 https://zenodo.org/record/7022648 https://doi.org/10.5281/zenodo.7022648 eng eng doi:10.5281/zenodo.6966936 https://zenodo.org/record/7022648 https://doi.org/10.5281/zenodo.7022648 oai:zenodo.org:7022648 info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode Machine Learning Weather MLOps Pipeline info:eu-repo/semantics/other dataset 2022 ftzenodo https://doi.org/10.5281/zenodo.702264810.5281/zenodo.6966936 2023-03-11T04:31:44Z This record is intended as sample data for a Walkthrough at the UK RSE 2022 Conference titled "MLOps for RSEs". The code that uses this sample dataset can be found on GitHub. There are 2 parts based on the sample problems in the walkthrough Classifying wind rotor events Clustering weather regimes Rotors Dataset This dataset is intended as a machine learning dataset, to train a model to predict the occurrence of turbulent wind gusts called "rotors". These are wind gusts happening on the leeward side of mountains. When they occur near an airfield, this can be hazardous from aviation operations. This data is intended to be used with the code on the Met Office Data Science Community of Practice GitHub repository. Files: 2021_met_office_aviation_rotors.csv - Raw dataset 2021_met_office_aviation_rotors_preprocessed.csv - Preprocessed dataset ready for machine learning rotors_catalog.yml - Intake Catalog file for the rotors dataset. More Information: MO Data Science Community of Practice GitHub - https://github.com/MetOffice/data_science_cop/tree/master/challenges/2021_falklands_rotors Met Office Youtube - What are rotors? https://www.youtube.com/watch?v=jgSZG9SqN_s What are Lee Waves? https://www.metoffice.gov.uk/weather/learn-about/weather/types-of-weather/wind/lee-waves\ Weather Regime Clustering This dataset is a UK and North Atlantic cutout of the Mean Sea-level Pressure (MSLP) field in ERA5 reanalysis dataset produced by ECMWF. This dataset is used for demonstrating an unsupervised learning pipeline. Files: era5_mslp_UK_2017_2020.nc - Gridded dataset of ERA5 reanalysis data. Dataset North Atlantic Zenodo |
institution |
Open Polar |
collection |
Zenodo |
op_collection_id |
ftzenodo |
language |
English |
topic |
Machine Learning Weather MLOps Pipeline |
spellingShingle |
Machine Learning Weather MLOps Pipeline Stephen Hadadad UK RSE Conference 2022 Walkthrough - MLOps for RSEs - Sample Data |
topic_facet |
Machine Learning Weather MLOps Pipeline |
description |
This record is intended as sample data for a Walkthrough at the UK RSE 2022 Conference titled "MLOps for RSEs". The code that uses this sample dataset can be found on GitHub. There are 2 parts based on the sample problems in the walkthrough Classifying wind rotor events Clustering weather regimes Rotors Dataset This dataset is intended as a machine learning dataset, to train a model to predict the occurrence of turbulent wind gusts called "rotors". These are wind gusts happening on the leeward side of mountains. When they occur near an airfield, this can be hazardous from aviation operations. This data is intended to be used with the code on the Met Office Data Science Community of Practice GitHub repository. Files: 2021_met_office_aviation_rotors.csv - Raw dataset 2021_met_office_aviation_rotors_preprocessed.csv - Preprocessed dataset ready for machine learning rotors_catalog.yml - Intake Catalog file for the rotors dataset. More Information: MO Data Science Community of Practice GitHub - https://github.com/MetOffice/data_science_cop/tree/master/challenges/2021_falklands_rotors Met Office Youtube - What are rotors? https://www.youtube.com/watch?v=jgSZG9SqN_s What are Lee Waves? https://www.metoffice.gov.uk/weather/learn-about/weather/types-of-weather/wind/lee-waves\ Weather Regime Clustering This dataset is a UK and North Atlantic cutout of the Mean Sea-level Pressure (MSLP) field in ERA5 reanalysis dataset produced by ECMWF. This dataset is used for demonstrating an unsupervised learning pipeline. Files: era5_mslp_UK_2017_2020.nc - Gridded dataset of ERA5 reanalysis data. |
format |
Dataset |
author |
Stephen Hadadad |
author_facet |
Stephen Hadadad |
author_sort |
Stephen Hadadad |
title |
UK RSE Conference 2022 Walkthrough - MLOps for RSEs - Sample Data |
title_short |
UK RSE Conference 2022 Walkthrough - MLOps for RSEs - Sample Data |
title_full |
UK RSE Conference 2022 Walkthrough - MLOps for RSEs - Sample Data |
title_fullStr |
UK RSE Conference 2022 Walkthrough - MLOps for RSEs - Sample Data |
title_full_unstemmed |
UK RSE Conference 2022 Walkthrough - MLOps for RSEs - Sample Data |
title_sort |
uk rse conference 2022 walkthrough - mlops for rses - sample data |
publishDate |
2022 |
url |
https://zenodo.org/record/7022648 https://doi.org/10.5281/zenodo.7022648 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_relation |
doi:10.5281/zenodo.6966936 https://zenodo.org/record/7022648 https://doi.org/10.5281/zenodo.7022648 oai:zenodo.org:7022648 |
op_rights |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode |
op_doi |
https://doi.org/10.5281/zenodo.702264810.5281/zenodo.6966936 |
_version_ |
1766133063743438848 |