UK ONS-UNECE Machine Learning Group 2022 webinar

November 30, 2022

Machine learning (ML) is drawing increasing attention among statistical organisations. ML can help carry out tasks that used to be carried out by humans such as reading and understanding textual data. This allows statistical organisations to perform manual tasks in a more efficient manner. ML is also an indispensable tool for processing and analysing the vast amount of information in big data, enabling the production of statistics on a more disaggregated level as well as new types of statistical products.

As statistical organisations explore ML they can benefit from sharing knowledge and experience, and from collaborating on developing common solutions. The ONS-UNECE Machine Learning Group 2022 is an initiative which brings together 420 members from 65 different organisations. The group has seven theme groups focusing on different ML application areas (web-scraping data, text classification, imagery data analysis, AIS data analysis) as well as cross-cutting issues arising from the integration of ML into the production processes of statistical organisations (quality of training data, IT infrastructure and model retraining).

Drawing on the group’s work in 2022, the webinar shared the results, lessons and discussions from the theme groups to offer insight into how machine learning can be applied to improve statistical production.  It also explore some approaches to common challenges experienced in deploying ML models in statistical systems.

The webinar provided an opportunity for the statistical community to learn about the highlights of the group’s work in 2022 as well as the latest developments in machine learning in statistical organisations internationally.

The webinar recording is now available here .


Session I: Application areas of ML

Start (CET)

Description

Speaker

10:00

Welcome + Opening Remarks

Eric Deeben (chair; UK, ONS)

Taeke Gjaltema (UNECE)

10:05

Introduction to the ML Group and overview of 2022 programme

Eric Deeben and Alison Baily (UK, ONS)

10:15

Applications I: Web scraping data

Michael Reusens (Statistics Flanders), Klaudia Peszat (Statistics Poland) and Bilal Kurban (Turkish Statistical Institute)

10:40

Q&A / Discussion


10:50

Applications II: Text Classification

InKyung Choi (UNECE)

11:00

Applications III: Imagery data

Joep Burger (Statistics Netherlands) and Nova Sharkey (Statistics Ireland)

11:10

Applications IV: AIS data

Justin McGurk (Central Statistics Office, Ireland) and Gabriel Fuentes (Norwegian School of Economics)

11:20

Q&A / Discussion

Poll results

Q&A

 Session II: Cross-cutting issues for ML in production

Start (CET)

Description

Speaker

15:00

Welcome

Eric Deeben (chair; UK, ONS)

15:05

Introduction to the ML Group and overview of 2022 programme (recap)

Eric Deeben and Alison Baily (UK, ONS)

15:10

ML In Statistical Production Processes I:  Quality of Training Data

Marco Puts (Statistics Netherlands)

15:30

Q&A / Discussion


15:40

ML In Statistical Production Processes II: Model retraining

Andrea Del Monaco (Bank of Italy)

16:00

ML In Statistical Production Processes III: Infrastructure

Jakob Engdahl (Statistics Sweden)

16:15

Q&A / Discussion

Poll results

Q&A

16:30

Closing remarks


Mary Gregory (UK, ONS)


Note that the webinar is held as a side event of the High-Level Group on Modernisation of Official Statistics (HLG-MOS) 2022 Workshop

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