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You take a real situation with real data, messy as that is, and build a model that works to explain the behavior of real data".
Many of these operations rely on something as simple as an Excel spreadsheet and a hodgepodge of tools thrown together, making the data messy and the process complicated.
Similar(58)
Most scientists have messy data, contradictory data, incomplete data, ambiguous data.
"Geological data are messy, by necessity.
Data is messy, and learners should not always be introduced to it through a clean, static data set but through encountering the complex process of collection.
It's tough to launch new analytics-based business models if your data is messy or your processes are not integrated.
The data are messy, Mr Graham says, but by and large the geoweb is a lot thicker in rich places than in poor ones, and thickest of all in the Nordic countries (see map, next page).
Crime data is messy data, collected by humans.
CrunchBase's category data is messy and most large companies like Apple could be classified several ways so this data is not precise (see pie chart at top).
While data is messy and sometimes defies automation techniques, this should provide a good head start if it works as described.
These patterns allow us to ask why different individuals show these different disease trajectories". Saria notes that working to develop models means "doing a deep dive to really understand all the ways in which the data are messy.
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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