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Ep.93 Michelle Conway and Sarah Schlobohm- Machine Learning in the Real World Lessons from the Experts

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Welcome to another captivating episode of the Women in Data® Podcast! Today Karen is joined by two exceptional experts in the field: Michelle Conway, Lead Data Scientist at Lloyds Banking Group, and Sarah Schlobohm, Head of AI and Particle Physicist. Together they discuss the world of Machine Learning Ops.
A central theme of the discussion revolves around the lifecycle of MLOps and the concept of Machine Learning as a "solution to a problem”. Michelle, Sarah and Karen delve into this idea, stressing the importance of identifying the right opportunities for Machine Learning to truly be effective. They discuss how businesses can avoid falling into the trap of implementing ML without a clear understanding of appropriate applications.
They also highlight how Machine Learning doesn't operate in isolation but requires seamless integration with other data departments, such as data governance. This comprehensive approach ensures that ML initiatives are well-aligned with the overall data strategy of the organisation, leading to more successful outcomes.
This episode is a must-listen for anybody looking to learn more about ML Ops and the potential applications of this exciting field.

  continue reading

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Manage episode 380198722 series 2872468
Sisällön tarjoaa womenindata. womenindata tai sen podcast-alustan kumppani lataa ja toimittaa kaiken podcast-sisällön, mukaan lukien jaksot, grafiikat ja podcast-kuvaukset. Jos uskot jonkun käyttävän tekijänoikeudella suojattua teostasi ilman lupaasi, voit seurata tässä https://fi.player.fm/legal kuvattua prosessia.

Welcome to another captivating episode of the Women in Data® Podcast! Today Karen is joined by two exceptional experts in the field: Michelle Conway, Lead Data Scientist at Lloyds Banking Group, and Sarah Schlobohm, Head of AI and Particle Physicist. Together they discuss the world of Machine Learning Ops.
A central theme of the discussion revolves around the lifecycle of MLOps and the concept of Machine Learning as a "solution to a problem”. Michelle, Sarah and Karen delve into this idea, stressing the importance of identifying the right opportunities for Machine Learning to truly be effective. They discuss how businesses can avoid falling into the trap of implementing ML without a clear understanding of appropriate applications.
They also highlight how Machine Learning doesn't operate in isolation but requires seamless integration with other data departments, such as data governance. This comprehensive approach ensures that ML initiatives are well-aligned with the overall data strategy of the organisation, leading to more successful outcomes.
This episode is a must-listen for anybody looking to learn more about ML Ops and the potential applications of this exciting field.

  continue reading

100 jaksoa

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