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Contenuto fornito da IRMS, James Lappin, and Heather Jack. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da IRMS, James Lappin, and Heather Jack o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.
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IRMS020 - Machine learning club

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Manage episode 264488805 series 1020002
Contenuto fornito da IRMS, James Lappin, and Heather Jack. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da IRMS, James Lappin, and Heather Jack o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.
In this podcast Mark Bell (TNA) and Leontien Talboom (UCL and TNA) describe the machine learning club they have set up at the UK National Archives (TNA) to help archivists at TNA develop their AI literacy. They describe how they have taken the group through a series of stages to introduce them to data science, to give them experience of preparing data, and to enable them to develop their intuitions about how different machine learning models work (Naive Bayes, Support vector machines etc.), and an understanding of the challenges that AI can (and can't) be used to tackle. They also describe how they intend to move on to discuss some key issues in the application of AI to records, including the issue of the explainability of AI decisions and the issue of capturing the machine learning model itself as a record. Mark Bell is Senior digital researcher at TNA. Leontien Talboom is a doctoral researcher working with UCL's Department of Information Studies and with TNA. Mark and Leontien were interviewed by James Lappin on 22 May 2020. Links: Mark Bell profile: https://www.nationalarchives.gov.uk/about/our-research-and-academic-collaboration/our-research-and-people/staff-profiles/mark-bell/ Leontein Talboom profile: https://www.ucl.ac.uk/information-studies/leontien-talboom James Lappin blog https://thinkingrecords.co.uk/
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22 episodi

Artwork
iconCondividi
 
Manage episode 264488805 series 1020002
Contenuto fornito da IRMS, James Lappin, and Heather Jack. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da IRMS, James Lappin, and Heather Jack o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.
In this podcast Mark Bell (TNA) and Leontien Talboom (UCL and TNA) describe the machine learning club they have set up at the UK National Archives (TNA) to help archivists at TNA develop their AI literacy. They describe how they have taken the group through a series of stages to introduce them to data science, to give them experience of preparing data, and to enable them to develop their intuitions about how different machine learning models work (Naive Bayes, Support vector machines etc.), and an understanding of the challenges that AI can (and can't) be used to tackle. They also describe how they intend to move on to discuss some key issues in the application of AI to records, including the issue of the explainability of AI decisions and the issue of capturing the machine learning model itself as a record. Mark Bell is Senior digital researcher at TNA. Leontien Talboom is a doctoral researcher working with UCL's Department of Information Studies and with TNA. Mark and Leontien were interviewed by James Lappin on 22 May 2020. Links: Mark Bell profile: https://www.nationalarchives.gov.uk/about/our-research-and-academic-collaboration/our-research-and-people/staff-profiles/mark-bell/ Leontein Talboom profile: https://www.ucl.ac.uk/information-studies/leontien-talboom James Lappin blog https://thinkingrecords.co.uk/
  continue reading

22 episodi

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