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Module

Demonstrating adaptive learning

Archived

4 Topics

35 mins

 Pega Customer Decision Hub 8.3 Visible to: All users
Beginner Pega Customer Decision Hub 8.3 English
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To demonstrate that adaptive models learn from customer interactions when real-time data is not available, use a Monte Carlo data set to create mock customer data and train the models by using data flows. A data flow is a scalable and resilient data pipeline that ingests, processes, and moves data from one or more sources to one or more destinations.

After completing this module, you should be able to:

Use a Monte Carlo data set as mock customer data
Run a Make Decision data flow to generate Next-Best-Action decisions
Run a Capture Response data flow to simulate customer responses and train adaptive models
Demonstrate that adaptive models accurately pick up on strong predictors of customer behavior

Available in the following mission:

Data Scientist v1

Topics

Generating data using Monte Carlo data sets

5 mins

Extending a Monte Carlo data set

5 mins

Capturing customer responses

5 mins

Demonstrating adaptive learning

15 mins

Module Quiz

5 mins

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