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Beginner Pega Customer Decision Hub 8.8 Decision Management English

Machine Learning Operations (MLOps) is an approach that streamlines the process of building, testing, and deploying machine learning models. As a data scientist involved in a Pega Customer Decision Hub™ project, MLOps can help you manage the complexity of the machine learning pipeline.

In the business operation environment, you can add potential predictors to adaptive models and you can deploy new predictive models in shadow mode. In shadow mode, you can monitor the performance of a new model on production data without impacting business outcomes. Once the new model performs well, you can promote it to active status.

By utilizing MLOps best practices, you ensure that your models are robust, reliable, and integrate easily into the larger Customer Decision Hub ecosystem.

After completing this module, you should be able to:

Modify adaptive models.
Deploy a new predictive model in shadow mode.
Promote the new model to the active model status.
Promote a shadow model to the active status.

Practice what you learned in the following Challenges:

Adding predictors to an adaptive model in BOE Replacing a predictive model Promoting a shadow model to active status

Available in the following mission:

AI for 1:1 Customer Engagement

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