10. Data Science Workspace - Churn Prediction Model
In this module, you'll learn how to create a Machine Learning model that predicts a customer's likelihood to churn.
- Learn basic Data Science concepts and terminology
- Explore Adobe Experience Platform Data Science Workspace
- Analyze and transform your data.
- Author a model and operationalize it
- Train your model and experiment
- Build and Publish a Recipe.
- Access to Adobe Experience Platform: https://experience.adobe.com/platform
- Access to the zip file containing the three required notebooks
- This documentation has been created to facilitate hands-on, technical enablement around Adobe Experience Platform. In order to complete some of the modules, you'll need to change some variables and replace them by your specific Environment Variables . Please contact your Adobe contact who will provide you with the required Environment Variables of your specific Adobe Experience Platform instance.
This tutorial was created to facilitate a particular workshop format. It uses specific systems and accounts to which you might not have access. Even without access, we think you can still learn a lot by reading through this very detailed content. If you're a participant in one of the workshops and need your access credentials, please contact your Adobe representative who will provide you with the required information.
Have a look at the below architecture, which highlights the components that will be discussed and used in this module.
Sandbox to use
For this module, please use this sandbox: --aepSandboxId-- .
Don't forget to install, configure and use the Chrome Extension as referenced in 0.5 - Install the Chrome extension for the Experience League documentation
Learn about basic concepts and terminology used in the data science world.
One of the first steps in any data science project is Data Preparation. A Data Scientist has to ensure data is correct before feeding it into a model.
In this exercise, a Data Scientist creates the Target variable and create some independent, explanatory variables to add as inputs to the model.
In this exercise, you'll convert the feature engineering and model that you have prepared in the above steps into a recipe.
Summary of this module and overview of the benefits.
Thank you for investing your time in learning all there is to know about Adobe Experience Platform. If you have questions, want to share general feedback of have suggestions on future content, please contact Wouter Van Geluwe directly, by sending an email to firstname.lastname@example.org .