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UK ONS-UNECE Machine Learning Group 2021 webinar will be held virtually on 19th November 13:00 - 17:00 CET (convert this to your local time)


Note that the webinar is held as a side event of the High-Level Group on Modernisation of Official Statistics (HLG-MOS) 2021 Workshop


PROGRAMME

* time is in Central European Time (CET), click here to check the time in your local timezone

** programme is subject to change, all documents will be uploaded as they become available

Time (CET)TitleSpeakersDocuments
13:00Welcome and Project Overview

Eric Deeben (Head of International, Data Science Campus, ONS, UK)

Louisa Nolan (Chief Data Scientist, Data Science Campus, ONS, UK)


13:15

Guest Panel: Strategic Priorities for Machine Learning in the work of National Statistics Offices

Louisa Nolan (ONS, UK)

Sevgui Erman (Statistics Canada; Director and Chief Data Scientist)

Jakob Engdahl (Statistics Sweden; Senior Strategist)


Presentation (Statistics Canada)

Work Stream 1. Pilot studies: from Idea to Valid Solutions
13:40The Utilisation of Satellite Imagery Analysis for Poverty Mapping in Indonesia Arie Wahyu (Statistics Indonesia)Presentation
13:55Exploring Model-Assisted Machine Learning Estimates of Consumer ExpendituresClayton Knappenberger (US, Census Bureau) Presentation
14:10

A Shared Service for Text Classification

Klaus Lehmann (Chile, INE)Presentation
14:25Q&A

14:40Live poll for ML application areas

14:45Break
Work Stream 2. From Valid Solution to Production / Work Stream 3. Data Ethics and Governance
14:55Use Cases applied to a Data Lake Prototype in a National Statistical OfficeAbel Coronado (Mexico, INEGI)Presentation
15:10Ethical Consideration in the Use of Machine Learning for Research and Statistics Alice Toms (UK, Statistics Authority)Presentation
15:25Q&A

Work Stream 4. On the Quality of Training Data / Work Stream 5. On the Quality Framework for Statistical Algorithm 
15:35From Theory to Practice: Detecting Model DecayRiitta Piela (Statistics Finland)Presentation
15:50Holistic Approaches to Evaluating a Machine Learning Model: A case study for automated coding Jose Jiminez (Mexico, INEGI)Presentation
16:05Q&A

16:15Break
Machine Learning Group - the way forward
16:20Future work presentationAlison Baily (UK, ONS) and InKyung Choi (UNECE)
16:30Discussion

16:50Wrap up and conclusion

ABOUT THE WEBINAR

Many National Statistical Offices (NSOs) are exploring how machine learning (ML) can be used to increase the relevance and quality of official statistics in an environment of growing demands for trusted information, rapidly developing and accessible technologies, and numerous competitors. While the specific business environments may vary depending on the country, NSOs face similar types of challenges which can benefit from sharing knowledge, experiences and collaborating on developing common solutions within the broad official statistical community.

Building on the work of the UNECE HLG-MOS Machine Learning Project (2019-2020), the UK Office for National Statistics Data Science Campus, in partnership with the UNECE HLG-MOS, launched a new international initiative, the Machine Learning Group 2021, in January this year. The Group aims to:

  • Facilitate the creation, development and implementation of research projects and skill-building activities that meet the global statistical community’s needs.
  • Build and engage a strong machine learning community by sharing resources and good practice, exchanging ideas and experiences, and keeping abreast of developments in the field.
  • Offer open, shareable, and easily accessible resources to the community; and
  • Facilitate machine learning capacity building for official statistics.

As machine learning revolutionises the work of national statistical organisations (NSOs), the Machine Learning Group 2021 webinar will offer insight and ideas for new research into how machine learning can be deployed in NSOs. 

The webinar will provide an opportunity to learn about the progress that the Group has made this year in its different work areas, from coding and classification and satellite imagery to operationalisation and data ethics. Bringing together colleagues from across the global official statistics community, it will include contributions from senior figures in the data science divisions of various NSOs as well as discussion on the priorities for advancing the use of machine learning in official statistics in 2022.

If you have any questions about the event, please contact sarah.phelps at ons.gov.uk or ML2021 at ons.gov.uk



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