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Under such circumstances, they normally overlook security concerns and stick to being feature complete on their products.
As it stands, my default inclination is to think of the exploratory estimation methods as being "feature extractions" in pattern recognition (i.e. a data dimension reduction step).
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I admire ReadNotify's ingenuity in presenting booby-trapped messages as being feature-rich.
Google needs to worry about being feature-inferior, since that would indicate laziness and monopoly.
The API will bring Dropbox closer to being able to truly compete with Box in the enterprise, but Box CEO Aaron Levie tells me being feature-complete goes beyond security.
Along with being feature-rich, SLIMS' power comes from being able to handle longitudinal data from multiple time-points and biological sources.
This is feature journalism masquerading as history.
Facebook is feature heavy.
It's feature time.
The key to quality is feature extraction.
The second part is feature selection.
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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