In Level 2, we look at the architecture and structure of the Machine Learning Services server process.
This first installment of the Stairway to Machine Learning Services explains the installation process for this subsystem in SQL Server.
This is a series designed to help you learn more about Machine Learning Services using both R and Python. We will cover the architecture, installation, configuration, and use of Machine Learning Services to run complex analysis on your data.
In the final article in this series, Robert Sheldon demonstrates combining data sources with multiple formats into one Python data frame.
Visualization is often the first step in analyzing data. Python makes visualization easy. In this article, Robert Sheldon demonstrates how to generate multiple charts from one dataset using Python with SQL Server Machine Learning Services.
Python is widely used to analyze data. One such use is to find anomalies or outliers. In this article, Robert Sheldon demonstrates how to create a support vector machine (SVM) to score test data so that outliers can be viewed on a scatter plot.
One of the advantages of running Python from SQL Server is the ability to create graphics to assist in analysis of data. Robert Sheldon demonstrates matplotlib, a 2D plotting library, widely used with Python to create quality charts.