Demonstrating adaptive learning

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.

Beginner

Inglese

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

Disponibile nelle seguenti missioni:

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