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 2017
Contents
About this sample
Before you begin
Sample details
Related links
About this sample
Predictive modeling is a powerful way to add intelligence to your application. It enables applications to predict outcomes against new data. The act of incorporating predictive analytics into your applications involves two major phases: model training and model operationalization.
In this sample, you will learn how to create a predictive model in python and operationalize it with 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
- Authors: Nellie Gustafsson
- Update history: Getting started tutorial for SQL Server ML Services - Python
Before you begin
To run this sample, you need the following prerequisites:
Download a DB backup file and restore it using Setup.sql. Download DB
Software prerequisites:
- SQL Server 2017 CTP2.0 (or higher) with Machine Learning Services (Python) installed
- SQL Server Management Studio
- Python Tools for Visual Studio
Run this sample
- From SQL Server Management Studio or SQL Server Data Tools connect to your SQL Server vNext database and execute setup.sql to restore the sample DB you have downloaded
- From SQL Server Management Studio or SQL Server Data Tools, open the Predictive Model Python.sql script
This script sets up:
Necessary tables
Creates stored procedure to train a model
Creates a stored procedure to predict using that model
Saves the predicted results to a DB table - You can also try the python script on its own. Just remember to point the Python environment to the corresponding path "C:\Program Files\Microsoft SQL Server\MSSQL14.MSSQLSERVER\PYTHON_SERVICES" if you run in-db Python Server, or "C:\Program Files\Microsoft SQL Server\140\PYTHON_SERVER" if you have the standalone Machine Learning Server installed.
Sample details
This sample shows how to create a predictive model with Python and generate predictions using the model and deploy that in SQL Server with SQL Server Machine Learning Services.
rental_prediction.py
The Python script that generates a predictive model and uses it to predict rental counts
rental_prediction.sql
Takes the Python code in Predictive Model.py and deploys it inside SQL Server. Creating stored procedures and tables for training, storing models and creating stored procedures for prediction.