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icp4d-customer-churn-classifier - Infuse AI into your application

  •    Jupyter

In this code pattern, we will create and deploy a customer churn prediction model using IBM Cloud Private for Data. First, we will load customer demographics and trading activity data into Db2 Warehouse. Next, we'll use a Jupyter notebook to visualize the data, build hypotheses for prediction, and then build, test, and save a prediction model. Finally, we will enable a web service and use the model from an app. The use case describes a stock trader company that can use churn prediction to target offers for at-risk customers. Once deployed, the model can be used for inference from an application using the REST API. A simple app is provided to demonstrate using the model from a Python app.

db2-event-store-akka-streams - Use Akka to implement a WebSockets endpoint and stream data to Db2 Event Store

  •    Jupyter

In this code pattern, we will build a Scala app that uses Akka to implement a WebSockets endpoint which streams data to a Db2 Event Store database. For our data, we'll use online retail order details in CSV format. We'll use Jupyter notebooks with Scala and Brunel to visualize the Event Store data. Install IBM® Db2® Event Store Developer Edition on Mac, Linux, or Windows by following the instructions here.

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