Introduction-to-churn-prediction.txt

Ian Swanson
Ian Swanson
CEO & Founder DataScience.com
5d
Introduction to Churn Prediction in Python
Tutorial here ---> http://bit.ly/2Ij82hD

This tutorial provides a step-by-step guide for predicting churn using Python. Boosting algorithms are fed with historical user information in order to make predictions. This type of pipeline is a basic predictive technique that can be used as a foundation for more complex models.

This post was contributed by Seyed Sajjadi. Seyed is a data scientist at Electronic Arts (EA). His general research interest lies primarily in the theory and application of artificial intelligence, specifically in cognitive architectures, machine learning, computer vision, and robotics. 

Thanks for sharing with the data science community Seyed!

Tutorial here ---> http://bit.ly/2Ij82hD

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