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"...and the moment you run into this will tell you a lot about how you feel as a person, to learn something you might have been wrong about." -Tom Carmichael
Tom is the Chief Data Scientist at Datarock and we spent a long time at the beginning of this episode talking about the fields of mathematical and computational geology, particularly from the perspective of someone at the university level that is interested in getting into these fields. The rest of the show is about Tom losing his membership to the AGU and a lot of Q&A on the concept of spatial autocorrelation - and importantly how it applies to geochemical data.
For this episode we read: Importance of spatial predictor variable selection in machine learning applications - Moving from data reproduction to spatial prediction by Meyer et al., 2019.
5
33 ratings
"...and the moment you run into this will tell you a lot about how you feel as a person, to learn something you might have been wrong about." -Tom Carmichael
Tom is the Chief Data Scientist at Datarock and we spent a long time at the beginning of this episode talking about the fields of mathematical and computational geology, particularly from the perspective of someone at the university level that is interested in getting into these fields. The rest of the show is about Tom losing his membership to the AGU and a lot of Q&A on the concept of spatial autocorrelation - and importantly how it applies to geochemical data.
For this episode we read: Importance of spatial predictor variable selection in machine learning applications - Moving from data reproduction to spatial prediction by Meyer et al., 2019.
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