SQL Server data science walkthroughs using R, Python and T-SQL
These walkthroughs use SQL Server, SQL Server R Services, and SQL Server Python Services to do predictive analytics. R and Python code is deployed in stored procedures. They follow the steps outlined in the Team Data Science Process. For an overview of the Team Data Science Process, see Data Science Process.
Additional data science walkthroughs that execute the Team Data Science Process are grouped by the platform that they use. See Walkthroughs executing the Team Data Science Process for an itemization of these examples.
Predict taxi tips using Python and SQL queries with SQL Server
The Use SQL Server walkthrough shows how you build and deploy machine learning classification and regression models using SQL Server and a publicly available NYC taxi trip and fare dataset.
Predict taxi tips using Microsoft R with SQL Server
The Use SQL Server R Services walkthrough provides data scientists with a combination of R code, SQL Server data, and custom SQL functions to build and deploy an R model to SQL Server. The walkthrough is designed to introduce R developers to R Services (In-Database).
Predict taxi tips using R from T-SQL or stored procedures with SQL Server
The Data science walkthrough for R and SQL Server provides SQL programmers with experience building an advanced analytics solution with Transact-SQL using SQL Server R Services to operationalize an R solution.
Predict taxi tips using Python in SQL Server stored procedures
The Use T-SQL with SQL Server Python Services walkthrough provides SQL programmers with experience building a machine learning solution in SQL Server. It demonstrates how to incorporate Python into an application by adding Python code to stored procedures.
For a discussion of the key components that comprise the Team Data Science Process, see Team Data Science Process overview.
For a discussion of the Team Data Science Process lifecycle that you can use to structure your data science projects, see Team Data Science Process lifecycle. The lifecycle outlines the steps, from start to finish, that projects usually follow when they are executed.
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