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

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Manage episode 306343274 series 2355587
内容由TWIML and Sam Charrington提供。所有播客内容(包括剧集、图形和播客描述)均由 TWIML and Sam Charrington 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

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.

  continue reading

700集单集

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Manage episode 306343274 series 2355587
内容由TWIML and Sam Charrington提供。所有播客内容(包括剧集、图形和播客描述)均由 TWIML and Sam Charrington 或其播客平台合作伙伴直接上传和提供。如果您认为有人在未经您许可的情况下使用您的受版权保护的作品,您可以按照此处概述的流程进行操作https://zh.player.fm/legal

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.

  continue reading

700集单集

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