Python tutorials for SQL Server Machine Learning Services

APPLIES TO: yesSQL Server noAzure SQL Database noAzure SQL Data Warehouse noParallel Data Warehouse

This article describes the Python tutorials and quickstarts 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.

Python tutorials

Tutorial Description
Predict ski rental with linear regression 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 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 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 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 Learn the basics of how to call Python in T-SQL.
Handle inputs and outputs using Python in SQL Server Learn how to handle inputs and outputs for Python in sp_execute_external_script.
Python data structures in SQL Server Shows how SQL Server uses the Python pandas package to handle data structures.
Train and use your first model Explains how to create, train, and use a Python model to predict new data.

Next steps