Classify US Incomes - TDSP Project

By for September 18, 2017

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How to use the Team Data Science Process template to create a project in Azure Machine Learning that classifies US incomes.
The **detailed documentation** for this real world scenario is below: []( For code samples, you can also click the **View Project** icon on the right and visit the project GitHub repository. ## Introduction Standardization of the structure and documentation of data science projects, that is anchored to an established [data science lifecycle](, is key to facilitating effective collaboration in data science teams. Creating Azure Machine Learning projects with the [Team Data Science Process (TDSP)]( template provides a framework for such standardization. Here we provide an example of how an actual machine learning project can be created using TDSP structure, populated with project-specific code, artifacts and documents, and executed within the Azure Machine Learning. ## Overview This sample shows how to instantiate and execute a machine learning project using the [Team Data Science Process (TDSP)]( structure and templates in Azure Machine Learning. For this purpose, we use the well-known [1994 US Census data from the UCI Machine Learning Repository]( The modeling task is to predict US annual income classes from US Census information (for example, age, race, education level, country of origin, etc.). Project summary is available in the [GitHub repository]( ## Pre-requisites * An Azure [subscription]( You can get a [free subscription]( to execute this sample also. * An [Azure Data Science Virtual Machine (DSVM) Windows Server 2016](, (VM Size: [DS3_V2](, with 4 virtual CPUs and 14-Gb RAM). Although tested on an Azure DSVM, it is likely to work on any Windows 10 machine.