Your browser is out of date

Update your browser to view this website correctly. Update my browser now


Watch Now

Understanding which of your customers are most likely to churn or unsubscribe from your services is one of the most powerful applications of machine learning (ML) in the enterprise. Understanding why and providing guidance on actions to prevent churn is where machine learning excels. Churn prediction is among the more common enterprise ML applications and has well-understood development patterns. The application of interpretability in order to understand which factors have the biggest influence and the use of visual apps to highlight that insight, providing corrective actions for the business, is a pattern that will provide value to your data science team. 


In this webinar you’ll learn:

  • About new Applied ML Templates for Cloudera Machine Learning (CML), which are adaptable sample workflows for enterprise ML applications.

  • How to use the Applied ML Template for Customer Churn applications in CML along with integrations from the Cloudera Fast Forward Labs Interpretability report

  • Instructions for using the Applied ML Template to deliver business value with CDP Public Cloud immediately


The presentation will feature a live demonstration of building a churn application that you can use for your organization. 



Cloud Machine Learning Specialist

Jeff Fletcher


Jeff is the field specialist for Cloudera Machine Learning and other cloud ML products. He holds a degree in electrical engineering from Witwatersrand University and has been involved in Internet technology for most of my professional life with a strong commercial focus. Before Cloudera, Jeff started his professional journey at Telkom in 1994, working on the initial Internet infrastructure in South Africa, then later founded Antfarm Networking Technologies, South Africa’s first streaming, and webcasting company.

Your form submission has failed.

This may have been caused by one of the following:

  • Your request timed out
  • A plugin/browser extension blocked the submission. If you have an ad blocking plugin please disable it and close this message to reload the page.