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Minitab Model Ops

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Minitab Model Ops is a machine learning operations (MLOps) platform that helps teams deploy predictive models, make their predictions available to applications, and monitor performance in production. It is intended for business analysts, engineers, data science teams, and organizations that need to use models beyond the development stage. Users can import supported models into a central repository and create deployments that expose predictions through API endpoints. Models developed in Minitab Statistical Software can be published to Model Ops, and predictions can be incorporated into other business applications. Teams can use Minitab Connect to send new data for scoring and return the predictions to a data table. This supports use cases such as process decisions, forecasting, and other workflows that rely on current model outputs. Key capabilities include: - A model repository for importing, organizing, deploying, and removing supported models. - API endpoints for serving predictions to connected applications and workflows. - Drift and stability reports for evaluating changes in model inputs and performance over time. - Alerts and deployment metrics, including model status, uptime, and response time. - API keys, user roles, and audit logs for controlling access and tracking changes. Model Ops supports champion and challenger models, allowing teams to compare alternatives within a deployment. Users can set thresholds and receive notifications when a model needs attention. The platform helps teams decide when to investigate, retrain, or replace a model as conditions change. It runs online and provides browser-based access to deployment and monitoring information. Minitab offers product documentation and tutorials for setting up integrations, managing deployments, and interpreting monitoring reports.

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