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As it progressed, the Machine Learning project was informed about other developments of ML to produce official statistics. In particular, during a series of virtual sessions held in October 2020, several speakers were invited to provide an introduction on ML developments conducted in their statistical organisations, It is important to note that they were not carried out within the ML project. The presentations are shared to further highlight the interest in advancing the use of ML.

Main statistical processDevelopmentData source
Text classificationBelgium Flanders - A better statistic on innovative companies in Flanders using web scraping and machine learningWeb scraped
OECD - SDG Financing Lab (to be shared) Administrative
UK - Automated classification of web scraped clothing data in consumer price statisticsWeb scraped
Survey write-in responses
Survey write-in responses
Switzerland - Automation of General Classification of Economic Activities coding - NOGAutoAll sources
Paper documents
Record linkage or matchingCanada - Machine Learning for Record Linkage at Statistics CanadaAll sources
USA BLS - Matching fatal injury records with supervised machine learningSurvey and administrative
Edit and Imputation

All sources
Census
Combination of sources
Administrative
Estimation and AnalysisCombination of sources
Aggregates
Switzerland - ML_SoSi: Individual trajectories in the social security systemCombination of sources



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