Sentence examples for deploying a model from inspiring English sources

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Simply deploying a model doesn't mean the project is done.

A multi-resolution analysis is then used to improve the blur assessment, deploying a model of neural pooling in cortical area V1 [18].

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As a result, a set of elements required for deploying a model-driven DR screening service has been established, namely: clinical concepts, archetypes, termsets, templates, guideline definition rules, and user interface definitions.

The finance unit in the global manufacturer (example four) has deployed a model that traditionally has worked for many business units: Develop analytics capabilities inside the division as it makes sense to improve the business.

Additional information requested for the model page was: specific instructions on how to deploy a model, a graphical representation of the model, and to what percentage each contributor participates in the development of a model.

Some examples include: tools like MLFlow that handle tracking of different experiment iterations, libraries like Keras that we can quickly use to build state of the art models, developer environments where data scientists can use notebooks on powerful compute machines without having to manage the infrastructure, and automated deployment tools that make it easy to deploy a model.

In this paper, we propose a thermal model, tModel, that projects outlet temperatures from inlet temperatures as well as directly measured multicore temperatures rather than deploying a utilization model.

The project will assess weather forecasting capabilities by deploying a forecasting model for the Finger Lakes region, and explore and implement more efficient data storage formats and retrieval algorithms.

This project seeks to translate the results by deploying a business model that will lead to revenue streams and a long-term infrastructure capable of translating the approach into a sustained program of practice in all Girl Scout troops and many other youth-focused organizations nationwide.

(3) Different taxi drivers might prefer different BEV ranges, thereby they should be allowed to select from diversified BEV models, instead of deploying a single vehicle model for the entire taxi fleet.

In the talk I'll present two healthcare cases studies where these high-accuracy GAMs discover surprising patterns in the data that would have made deploying a black-box model risky, and also discuss the importance of model intelligibility for dealing with fairness and trust issues such as race and gender bias.

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