Skip to main content

Module

The impact of machine learning

1 Topic

15 mins

Visible to all users
Beginner Pega Customer Decision Hub 8.7 Pega Customer Decision Hub 8.6 English

The boost in the success rate, also known as lift, that artificial intelligence (AI) achieves is an important business metric. To report on this metric, a data scientist can use predictions. Predictions add best practices to predictive models and use a control group as a benchmark to measure lift. Customers in the control group receive a random offer instead of the one selected by AI. The use of a control group also adds a degree of exploration to the exploitation of the models.

After completing this module, you should be able to:

Describe how predictions add best practices to predictive models
Explain how the use of a model control group allows the measurement of lift
Explain how the use of a model control group adds exploration to the exploitation of the models

Practice what you learned in the following Challenge:

Monitoring predictions

Available in the following missions:

Data Scientist AI for 1:1 Customer Engagement

We'd prefer it if you saw us at our best.

Pega Academy has detected you are using a browser which may prevent you from experiencing the site as intended. To improve your experience, please update your browser.

Close Deprecation Notice