Live Machine Learning Tutorial: Churn Prediction

Churn prediction is big business. It minimizes customer defection by predicting which customers are likely to cancel a service. Though originally used within the telecommunications industry, it has become common practice for banks, ISPs, insurance firms, and other verticals.

The prediction process is data-driven and often uses advanced machine learning techniques. In this webinar, we'll look at customer data, do some preliminary analysis, and generate churn prediction models – all with Spark machine learning (ML) and a Zeppelin notebook.

Spark’s ML library goal is to make machine learning scalable and easy. Zeppelin with Spark provides a web-based notebook that enables interactive machine learning and visualization.

In this tutorial, we'll do the following:

  • Review classification and decision trees
  • Use Spark DataFrames with Spark ML pipelines
  • Predict customer churn with Apache Spark ML decision trees
  • Use Zeppelin to run Spark commands and visualize the results


Carol McDonald

Industry Solutions Architect MapR

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