Moving Machine Learning from POC to Product

Recap Summary

We were delighted to be back meeting people again face to face in Edinburgh for our most recent Data Science Community event, delivered in partnership with The Data Lab and hosted by the University of Edinburgh at the impressive Bayes Centre.

The event was a sell-out with over 120 registrations prior to the event.

We were joined by Martin Thorn, Head of Data Science & Data Platform at abrdn for a presentation on ‘Moving Machine Learning from POC to product’

3 Main Takeaways:

  1. - Being able to demonstrate great outcomes is more important than the algorithms you used to get there
  3. - Simplify your ideas and make them easy to digest (under promise and over deliver!)
  5. - You don’t need vast amounts of data - The real trick is to get value out of what you already have


Anyone who was not able to make it along to the event, don’t worry we have you covered.

You can watch the entire talk in full again here. Livestreamed by

Pictures from the event:

Moving Machine Learning from POC to Product

Guest Bio:

Martin Thorn, abrdn’s Head of Data Science & Data Platform, specializes in the kind of Data Science that gets results. His career has seen him work within and lead high-profile data teams at organisations such as Scottish Power, Sky and Virgin Money. In these and in his current role, Martin has always focused on delivering organisation value through data projects firstly and foremostly.

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