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Highly-configurable models, avoid the entry levels with their Celeron-based processors and opt for the Centrino Duo, and you've got a pretty decent bang for your buck, especially with the SXGA 15.4″ LCD, built-in wireless, and 5.5-pound weight.
Depending on the application, possible solutions to overcome these problems include the use of parsimonious conceptual models, avoid the use of a fixed pre-defined model conceptualization, but apply a "top-down" or "downward" method to allow the model structure to be adjusted or inferred from available data and field evidence.
Deterministic models avoid the need to model each individual separately.
These models avoid most of the aforementioned problems associated with NLP resources.
Compared to classical parametric regression techniques, tree-based decision models avoid any distributional assumption.
Among their advantages, in vitro models avoid for instance the need to recruit volunteers for a specific study.
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The adoption of finite element models avoids analytical modeling or the simplification on geometry or materials.
We add the ability to determine utilisation from workload models, avoiding over-provisioning on the new cloud.
This process encompasses several aspects, such as analyzing descriptor co-occurrence in the different candidate models, avoiding redundant descriptor sets, and analyzing descriptor target relationships.
Nevertheless, the designed approach takes advantage of both models avoiding the drawbacks of each one and allowing a smooth motion of the robot.
Such an approach, rather innovative in animal science, allows the construction of complex models avoiding the use of non-linear differential equations.
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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