In this Lab we are going to build, train and deploy a Churn Prediction Model
using Amazon SageMaker .
This model will allow us to automatically understand if a call
is subject to churn or not.
We’ll then make use of Amazon SageMaker Endpoints
to host and provide access to the model.
Finally, we’ll make use of AWS Lambda to
invoke the Churn Prediction Endpoint with data relative to a new call.
The endpoint will return Churn if the call is subject to churn or Not Churn
otherwise.
The Churn Prediction Endpoint can be used to redirect incoming calls to appropriate queues.
AWS allows to build a managed contact centre by using an
Amazon Connect instance.
Once the contact centre is up and running, we’ll deploy a simple call
flow with two queues
Then, we’ll make use the Churn Prediction endpoint to decide to which queue a call should be routed.
An AWS account is required to run this Lab, but no prior AWS experience is required. Click here to get started with AWS!
In this Lab we will use Python to write the body of a Lambda Function, but no prior experience is required.
No prior experience with Machine Learning is required to complete this Lab.
Feel free to ask questions when in doubt and enjoy the workshop!