367: Building Data Pipelines for COVID-19 Modeling

Samuel Hinton joins us again for an important and timely discussion on data pipelines and the work he’s doing to aid research on COVID-19 with the COVID-19 Critical Care Consortium. We also talk about his new online courses and his continued research into dark matter.

An episode of the Super Data Science: ML & AI Podcast with Jon Krohn podcast, hosted by Jon Krohn, titled "367: Building Data Pipelines for COVID-19 Modeling" was published on May 20, 2020 and runs 77 minutes.

May 20, 2020 ·77m · Super Data Science: ML & AI Podcast with Jon Krohn

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Summary

Samuel Hinton joins us again for an important and timely discussion on data pipelines and the work he’s doing to aid research on COVID-19 with the COVID-19 Critical Care Consortium. We also talk about his new online courses and his continued research into dark matter. In this episode you will learn: Sam’s current work and COVID-19 Critical Care Consortium [4:22] The COVID data science pipeline and workflow [12:50] Sam’s second online course [36:22] Bayesian inference [43:06] Sam at DSGO Virtual [53:30] Sam’s work on dark matter [1:01:25] What is Sam reading right now? [1:09:14] Additional materials: www.superdatascience.com/367

Episode Description

Samuel Hinton joins us again for an important and timely discussion on data pipelines and the work he’s doing to aid research on COVID-19 with the COVID-19 Critical Care Consortium. We also talk about his new online courses and his continued research into dark matter. In this episode you will learn: Sam’s current work and COVID-19 Critical Care Consortium [4:22] The COVID data science pipeline and workflow [12:50] Sam’s second online course [36:22] Bayesian inference [43:06] Sam at DSGO Virtual [53:30] Sam’s work on dark matter [1:01:25] What is Sam reading right now? [1:09:14] Additional materials: www.superdatascience.com/367

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