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Head in the Clouds, Feet in the Data with Britt Bluemel
For this episode we read:
Using machine learning to estimate a key missing geochemical variable in mining exploration: application of the Random Forest algorithm to multi-sensor core logging data (Schnitzler et al., 2019)
A big difference between applied geochemistry and machine is the terminology, but once you start to chip away at this, like Britt, you will realize that the two disciplines are not so different.
Join us as we talk about dimensionality reductions, transformations, and workflows pre- and post- her introduction to the realm of data science. And talk about a really neat paper that used random forest to predict sodium for an alteration study.
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By Sam Scher
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For this episode we read:
Using machine learning to estimate a key missing geochemical variable in mining exploration: application of the Random Forest algorithm to multi-sensor core logging data (Schnitzler et al., 2019)
A big difference between applied geochemistry and machine is the terminology, but once you start to chip away at this, like Britt, you will realize that the two disciplines are not so different.
Join us as we talk about dimensionality reductions, transformations, and workflows pre- and post- her introduction to the realm of data science. And talk about a really neat paper that used random forest to predict sodium for an alteration study.
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