| title | SQL Server Python tutorials | Microsoft Docs |
|---|---|
| ms.prod | sql |
| ms.technology | machine-learning |
| ms.date | 04/15/2018 |
| ms.topic | tutorial |
| author | HeidiSteen |
| ms.author | heidist |
| manager | cgronlun |
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This article provides a list of tutorials and samples that demonstrate the use of Python with SQL Server 2017. Through these samples and demos, you will learn:
- How to run Python from T-SQL
- What are remote and local compute contexts, and how you can execute Python code using the SQL Server computer
- How to wrap Python code in a stored procedure
- Optimizing Python code for a SQL production environment
- Real-world scenarios for embedding machine learning in applications
For information about requirements and setup, see Prerequisites.
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Learn the basics of how to call Python in T-SQL, using the extensibility mechanism pioneered in SQL Server 2016.
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Create a machine learning model in Python using revoscalepy
This lesson demonstrates how you can run code from a remote Python terminal, using SQL Server compute context. You should be somewhat familiar with Python tools and environments. Sample code is provided that creates a model using rxLinMod, from the new revoscalepy library.
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In-Database Python analytics for SQL developers
This end-to-end walkthrough demonstrates the process of building a complete Python solution using T-SQL stored procedures. All Python code is included.
These samples and demos provided by the SQL Server development team highlight ways that you can use embedded analytics in real-world applications.
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Build a predictive model using Python and SQL Server
Learn how a ski rental business might use machine learning to predict future rentals, which helps the business plan and staff to meet future demand.
[!TIP] Now includes native scoring from Python models!
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Perform customer clustering using Python and SQL Server
Learn how to use the Kmeans algorithm to perform unsupervised clustering of customers.