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The research-physiotherapist collecting the baseline data was trained at performing the measurements in a standardized way and was blinded for treatment assignment.
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The reviewers who assessed and extracted data were trained in the use of the QUADAS checklist.
All nurses collecting data were trained together and the laboratory equipment used was calibrated to ensure standardization.
In such a view, it would be of greater biological relevance if "omics" data were trained in the context of protein-protein interactions [ 3, 9, 10].
That is accomplished almost entirely in a supervised fashion, where labeled data is training an appropriately built neural network.
Let 700 cases of the data be training set, and 204 cases be testing set.
The data collector was trained by the research team on methods of data collection.
Data recorders were trained in data entry protocols.
Four data enumerators were trained on appropriate data collection methods and norms for approaching respondents.
As data artists are trained to make data visualizations interactive, they empower business executives to ask "what if" questions and see the answers based on the available data.
Predictive programs are only as good as the data they are trained on, and that data has a complex history.
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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