Move trained models beyond notebooks

Deploy machine learning models with usable interfaces, then test, monitor, and integrate them into software solutions.

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What matters

Turning a trained model into a deployable service
Presenting model outputs through a usable interface
Integrating machine learning into an existing application

Benefits

Model serving and deployment support
Testing and monitoring as part of the deployment lifecycle
Interfaces that help stakeholders interact with model results

Evidence

Deployed a sticker sales forecasting model using Modal
Served and deployed a binary classification model using BentoML
Built and deployed a computer vision antelope classifier with a user interface

Questions

Can Silver integrate a trained model into an application?

Yes. His stated ML deployment capabilities include model deployment, testing, monitoring, and integration into software solutions.

Interested?

Contact the company through its original website.