---
title: Python tutorials
description: This article describes the Python tutorials for SQL Server Machine Learning Services. Learn how to run Python scripts. Build, train, and deploy Python models to SQL Server. Learn about remote and local compute contexts. Explore the Microsoft Python packages for data science and machine learning.
ms.prod: sql
ms.technology: machine-learning
ms.date: 09/04/2019
ms.topic: tutorial
author: dphansen
ms.author: davidph
monikerRange: ">=sql-server-2017||>=sql-server-linux-ver15||=sqlallproducts-allversions"
---
# Python tutorials for SQL Server Machine Learning Services
[!INCLUDE[appliesto-ss-xxxx-xxxx-xxx-md](../../includes/appliesto-ss-xxxx-xxxx-xxx-md.md)]

This article describes the Python tutorials and quickstarts for [SQL Server Machine Learning Services](../install/sql-machine-learning-services-windows-install.md).

+ Learn how to run Python scripts.
+ Build, train, and deploy Python models to SQL Server.
+ Learn about remote and local compute contexts.
+ Explore the Microsoft Python packages for data science and machine learning.

<a name="bkmk_pythontutorials"></a>

## Python tutorials

| Tutorial | Description |
|-|-|
| [Predict ski rental with linear regression](python-ski-rental-linear-regression.md) | Use Python and linear regression to predict the number of ski rentals. Use notebooks in Azure Data Studio for preparing data and training the model, and T-SQL for model deployment. |
| [Categorizing customers using k-means clustering](python-clustering-model.md) | Use Python to develop and deploy a K-Means clustering model to categorize customers. Use notebooks in Azure Data Studio for preparing data and training the model, and T-SQL for model deployment. |
| [Create a model using revoscalepy](use-python-revoscalepy-to-create-model.md) | Demonstrates how to run code from a remote Python client using SQL Server as compute context. The tutorial creates a model using **rxLinMod** from the **revoscalepy** library. |
| [Python data analytics for SQL developers](sqldev-in-database-python-for-sql-developers.md) | This end-to-end walkthrough demonstrates the process of building a complete Python solution using T-SQL. |

## Python quickstarts

If you are new to SQL Server Machine Learning Services, you can also try the Python quickstarts.

| Quickstart | Description |
|-|-|
| [Hello World in Python and SQL Server](quickstart-python-run-using-t-sql.md) | Learn the basics of how to call Python in T-SQL. |
| [Handle inputs and outputs using Python in SQL Server](quickstart-python-inputs-and-outputs.md) | Learn how to handle inputs and outputs for Python in [sp_execute_external_script](../../relational-databases/system-stored-procedures/sp-execute-external-script-transact-sql.md). |
| [Python data structures in SQL Server](quickstart-python-data-structures.md) | Shows how SQL Server uses the Python pandas package to handle data structures. |
| [Train and use your first model](quickstart-python-train-score-in-tsql.md) | Explains how to create, train, and use a Python model to predict new data. |

## Next steps

+ [What is SQL Server Machine Learning Services (Python and R)?](../what-is-sql-server-machine-learning.md)
+ [Python extension to SQL Server](../concepts/extension-python.md)