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I'm less concerned with this data since it doesn't matter to the model if the estimates are absolutely correct.
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The exceptional licence growth of last two years could not continue forever so we are not overly concerned with this one data point.
This paper is mainly concerned with the data governance aspect.
For the bulk of the post, they seem authentically concerned with that data.
Eliminativist philosophers therefore tend to be concerned with the data coming from the relevant brain and cognitive sciences.
First, we were concerned with the data and interpretations of causative sources of contamination based on the Sourcetracker software.
Both outcomes researchers and informaticians are concerned with information and data.
This paper is concerned with engineering data management in the manufacture of complex, made-to-customer-order capital plant.
This paper is concerned with scattered data approximation in high dimensions: Given a data set X⊂Rd of N data points xi along with values yi∈Rd′, i= 1,…,N, and viewing the yi as values yi= f xi) of some unknown function f, we wish to return for any query point x∈Rd an approximation ˜f(x) to y= f(x).
This paper is concerned with adaptive data clustering and classification/labeling when each sensor collects a set of unlabeled observations that are drawn from a known number of classes.
To this point, YotaScale isn't just concerned with historical data, it actually makes forward projections.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com