SQL Server advanced significantly when ML Services was introduced. In this chapter, we used ML Services to train a simple predictive model. Because of the relational nature of SQL Server, we used the R language, which is suitable for predictive modeling.
In the first section, we started by learning how to check whether ML Services is installed and which languages are supported. Having an installation of ML Services is not enough; it must be properly configured in conjunction with a SQL Server instance. We learned how to configure the whole environment for external languages.
In the second section, we created a physical database schema that can be used to maintain trained predictive models. Different versions of predictive models are usually kept for comparison, so we looked at two approaches to carry out machine learning model versioning.
In the third section, we created...
