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# Build a predictive model with SQL Server Python
# Build a predictive model with Python using SQL Server 2017 Machine Learning Services

This sample shows how to create a predictive model in Python and operationalize it with SQL Server vNext.

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<!-- Delete the ones that don't apply -->
- **Applies to:** SQL Server vNext
- **Applies to:** SQL Server 2017 CTP2.0 or higher
- **Key features:**SQL Server Machine Learning Services
- **Workload:** SQL Server Machine Learning Services
- **Programming Language:** T-SQL, Python
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**Software prerequisites:**

<!-- Examples -->
1. SQL Server vNext CTP2.0 (or higher) with Machine Learning Services (Python) installed
1. SQL Server 2017 CTP2.0 (or higher) with Machine Learning Services (Python) installed
2. SQL Server Management Studio
3. Python Tools for Visual Studio

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Service uses Tedious library for data access and built-in JSON functionalities that are available in SQL Server 2016 and Azure SQL Database.

<a name=disclaimers></a>

## Disclaimers
The code included in this sample is not intended demonstrate some general guidance and architectural patterns for web development.
It contains minimal code required to create a REST API.
You can easily modify this code to fit the architecture of your application.


<a name=related-links></a>

## Related Links
<!-- Links to more articles. Remember to delete "en-us" from the link path. -->

For additional content, see these articles:

[SQL Server R Services - Upgrade and Installation FAQ](https://msdn.microsoft.com/en-us/library/mt653951.aspx)
[Other SQL Server R Services Tutorials](https://msdn.microsoft.com/en-us/library/mt591993.aspx)
[Watch a presentation about predictive modeling in SQL Server, that also goes through this sample](https://www.youtube.com/watch?v=YCyj9cdi4Nk&feature=youtu.be)