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Building Blocks of Machine Learning at LEGO with Francesc Joan Riera - #533

2021-11-04 · 43 min · episode 533 · 14 entities

episode page audio

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    Building Blocks of Machine Learning at LEGO with Francesc Joan Riera - #533
  • → hosted by Sam Charrington person
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    Feed author/publisher: Sam Charrington
  • → discusses Science concept
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  • → discusses Technology company
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    Feed category: Tech News
  • → hosted by TWIML company
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    Feed author/publisher: TWIML

Entities found in this episode

concepts 6

  • mentioned Science concept
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    Feed category: Science
  • mentioned Tech News concept
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    Feed category: Tech News
  • discusses Science concept
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    Feed category: Science
  • discusses News concept
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    evidence rules-v4
    Feed category: News
  • discusses Tech News concept
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    Feed category: Tech News
  • mentioned LEGO concept
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    LEGO

companys 4

  • mentioned TWIML company
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    Feed author/publisher: TWIML
  • mentioned Technology company
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    Feed category: Technology
  • discusses Technology company
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    Feed category: Technology
  • hosted by TWIML company
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    Feed author/publisher: TWIML

persons 3

  • mentioned Francesc Joan Riera person
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    Building Blocks of Machine Learning at LEGO with Francesc Joan Riera - #533
  • mentioned Sam Charrington person
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    evidence rules-v4
    Feed author/publisher: Sam Charrington
  • hosted by Sam Charrington person
    0.55
    evidence rules-v4
    Feed author/publisher: Sam Charrington

podcasts 1

Episode description as stored
Today we’re joined by Francesc Joan Riera, an applied machine learning engineer at The LEGO Group.  In our conversation, we explore the ML infrastructure at LEGO, specifically around two use cases, content moderation and user engagement. While content moderation is not a new or novel task, but because their apps and products are marketed towards children, their need for heightened levels of moderation makes it very interesting.  We discuss if the moderation system is built specifically to weed out bad actors or passive behaviors if their system has a human-in-the-loop component, why they built a feature store as opposed to a traditional database, and challenges they faced along that journey. We also talk through the range of skill sets on their team, the use of MLflow for experimentation, the adoption of AWS for serverless, and so much more! The complete show notes for this episode can be found at twimlai.com/go/534.