Predicting Customer Churn with XGBoost & Apache Spark in AWS

October 9, 2018

In this video we will focus solely on XGBoost (a distributed machine learning algorithm) and the Telco Customer Churn Dataset to train and predict Customer Churn using automated Apache Spark ML pipelines manage by Qubole and their Notebooks. We will then explore productionizing the trained XGBoost ML pipeline behind a Customer Web Portal to perform real-time scoring of a customer and present tailored offers to preempt customer churn. Through this journey we will also cover the machine learning portability formats Predictive Model Markup Language (PMML) and Portable Format for Analytics (PFA) for model export.

Previous Video
Using Qubole as the Data Lake for Programmatic Advertising (Adobe Advertising Cloud)
Using Qubole as the Data Lake for Programmatic Advertising (Adobe Advertising Cloud)

Speaker: Tom Silverstrim, Sr. Manager of Adobe Media Optimizer, Adobe Ad Cloud Presentation: Qubole has be...

Next Video
Auto Tuning Twitter Hadoop Jobs (Or: Don’t Touch That Analytics Dial!) Data Platforms 2018
Auto Tuning Twitter Hadoop Jobs (Or: Don’t Touch That Analytics Dial!) Data Platforms 2018

Speakers: - Ben Pence, Software Engineer, Twitter - Anton Panasenko, Software Engineer, Twitter Presentati...