Baker Hughes Challenge - TAMU Datathon
We developed algorithms to select 2,500 sets from 500,000 data points, optimizing training efficiency and accuracy. Visual comparisons using graphs and histograms validated our improved model results.
We developed algorithms to select 2,500 sets from 500,000 data points, optimizing training efficiency and accuracy. Visual comparisons using graphs and histograms validated our improved model results.
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