One-stop-shop for Artificial Intelligence and Machine Learning for Official Statistics Project (AIML4OS) is an ESSnet collaborative project involving 16 countries, started on 1 April 2024 and will last 4 years. The overall aim is to develop a ‘One Stop Shop’ for AI and ML in official statistics; that is, a platform which provides a single entry point for ESS staff to access a coherent set of capabilities for implementing AI/ML based solutions. This will provide them with tailored guidance and assistance in deploying AI/ML solutions within adequate methodological and implementation frameworks. The project is developed through 13 WPs, 6 supporting implementation and 7 dedicated to use cases. The knowledge and the framework realised and use cases experiences developed by the Consortium will allow them to use AI/ML to enable the development of more efficient and effective ways to deliver growing demand on official statistics.
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AIML4OS
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- funathon-project1
funathon-project1 PublicRepository of the 1st funathon project (tabular data)
- funathon-project3
funathon-project3 PublicRepository of the 3rd funathon project (satellite data)
- WP7_landcover
WP7_landcover PublicLand cover classification at regional level (NUTS2) using CoSIA deep learning model on high resolution aerial images
Python 4
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- WP7-Crop-type-mapping Public Forked from IPAR99/CropType
Repository for AIML_CropMapper python codes.
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AIML4OS/WP8_AT_LLM_EditRules's past year of commit activity - WP8NL_Editing_RegionalEmployment Public
Contains R-code for an application by Statistics Netherlands. The aim is to assess whether or not a record needs correection
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AIML4OS/WP8NL_Editing_RegionalEmployment's past year of commit activity - WP9_S2_PL Public
Materials concerning the imputation of foreign tourists with the identification of their country of origin for the years 2018–2020.
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AIML4OS/AIML4OS.github.io's past year of commit activity - WP10_Cluster1_StatCodGen Public
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