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Data Brew Season 2 Episode 7: Interpretable Machine Learning

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Manage episode 296458298 series 2814833
Indhold leveret af Databricks. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Databricks eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

For our second season of Data Brew, we will be focusing on machine learning, from research to production. We will interview folks in academia and industry to discuss topics such as data ethics, production-grade infrastructure for ML, hyperparameter tuning, AutoML, and many more.
What does it mean for a model to be “interpretable”? Ameet Talwalkar shares his thoughts on IML (Interpretable Machine Learning), how it relates to data privacy and fairness, and his research in this field.
See more at databricks.com/data-brew

  continue reading

42 episoder

Artwork
iconDel
 
Manage episode 296458298 series 2814833
Indhold leveret af Databricks. Alt podcastindhold inklusive episoder, grafik og podcastbeskrivelser uploades og leveres direkte af Databricks eller deres podcastplatformspartner. Hvis du mener, at nogen bruger dit ophavsretligt beskyttede værk uden din tilladelse, kan du følge processen beskrevet her https://da.player.fm/legal.

For our second season of Data Brew, we will be focusing on machine learning, from research to production. We will interview folks in academia and industry to discuss topics such as data ethics, production-grade infrastructure for ML, hyperparameter tuning, AutoML, and many more.
What does it mean for a model to be “interpretable”? Ameet Talwalkar shares his thoughts on IML (Interpretable Machine Learning), how it relates to data privacy and fairness, and his research in this field.
See more at databricks.com/data-brew

  continue reading

42 episoder

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