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@AIML4OS

AIML4OS

One-stop-shop for Artificial Intelligence and Machine Learning for Official Statistics (AIML4OS)
README.md

AIML4OS Implementation

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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  1. funathon-project1 funathon-project1 Public

    Repository of the 1st funathon project (tabular data)

    Python 7 55

  2. funathon-project2 funathon-project2 Public

    Repository of the 2nd funathon project (NLP)

    Python 6 106

  3. funathon-project3 funathon-project3 Public

    Repository of the 3rd funathon project (satellite data)

    Python 5 30

  4. WP7_landcover WP7_landcover Public

    Land cover classification at regional level (NUTS2) using CoSIA deep learning model on high resolution aerial images

    Python 4

  5. WP10 WP10 Public

    This repository contains the work and outputs of Work Package 10 – “From Text to Code” within the project “Artificial Intelligence for Official Statistics (AIML4OS)”.

    Python 3

  6. WP9S2LU_Price WP9S2LU_Price Public

    Price indices with ML based imputation

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Repositories

Showing 10 of 53 repositories
  • WP7_landcover Public

    Land cover classification at regional level (NUTS2) using CoSIA deep learning model on high resolution aerial images

    AIML4OS/WP7_landcover's past year of commit activity
    Python 4 0 0 0 Updated Oct 17, 2026
  • WP13 Public

    Main repository of WP13 - synthetic data. Will mainly contain links to other resources.

    AIML4OS/WP13's past year of commit activity
    HTML 0 GPL-3.0 0 0 0 Updated Oct 16, 2026
  • WP12 Public
    AIML4OS/WP12's past year of commit activity
    Python 1 MIT 1 0 1 Updated Oct 16, 2026
  • WP10-Statcodgen_tutorial Public

    This repository contains a Statcodgen tutorial. This tool enables you to train and evaluate NLP models for any technology, as well as generate Zero Gen synthetic data for training purposes.

    AIML4OS/WP10-Statcodgen_tutorial's past year of commit activity
    Lua 0 0 0 0 Updated Oct 14, 2026
  • WP10-Cluster2-RAG Public

    This repository is for example pipelines for using LLMs for text classification tasks.

    AIML4OS/WP10-Cluster2-RAG's past year of commit activity
    Jupyter Notebook 0 1 0 0 Updated Oct 13, 2026
  • WP7-Crop-type-mapping Public Forked from IPAR99/CropType

    Repository for AIML_CropMapper python codes.

    AIML4OS/WP7-Crop-type-mapping's past year of commit activity
    Python 2 1 0 0 Updated Oct 10, 2026
  • WP10_Cluster4_MLOps Public

    MLOps tutorial for automatic coding in NSIs

    AIML4OS/WP10_Cluster4_MLOps's past year of commit activity
    TeX 2 0 2 0 Updated Oct 8, 2026
  • WP8_NO_OutlierDetection Public Forked from statisticsnorway/play-aiml-edit

    Project repository for grant on AIML4OS related to WP8 - data editing.

    AIML4OS/WP8_NO_OutlierDetection's past year of commit activity
    Python 0 MIT 1 0 0 Updated Oct 7, 2026
  • AIML4OS.github.io Public

    Homepage for AIML4OS project

    AIML4OS/AIML4OS.github.io's past year of commit activity
    R 2 1 1 0 Updated Oct 7, 2026
  • WP10_Cluster2_TransformerClassification Public
    AIML4OS/WP10_Cluster2_TransformerClassification's past year of commit activity
    R 0 CC0-1.0 0 0 0 Updated Oct 6, 2026
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