MLOps

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.

Anfänger

Decision Management

Englisch

Nach Abschluss dieses Moduls können Sie Folgendes:

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.

Üben Sie das Gelernte in den folgenden Challenges:

Adding predictors to an adaptive model in BOE v1 Replacing a predictive model v3 Promoting a shadow model to active status v1

In der folgenden Mission verfügbar:

AI for 1:1 Customer Engagement v2

Themen

Change management process

5 Min.

Prediction lifecycle

10 Min.

Adding predictors to an adaptive model in BOE

10 Min.

MLOps process

10 Min.

Placing a predictive model in shadow mode

10 Min.

Promoting shadow models to active status

10 Min.

Modulquiz

5 Min.