Book Image

SQL Server 2017 Machine Learning Services with R.

By : Julie Koesmarno, Tomaž Kaštrun
Book Image

SQL Server 2017 Machine Learning Services with R.

By: Julie Koesmarno, Tomaž Kaštrun

Overview of this book

R Services was one of the most anticipated features in SQL Server 2016, improved significantly and rebranded as SQL Server 2017 Machine Learning Services. Prior to SQL Server 2016, many developers and data scientists were already using R to connect to SQL Server in siloed environments that left a lot to be desired, in order to do additional data analysis, superseding SSAS Data Mining or additional CLR programming functions. With R integrated within SQL Server 2017, these developers and data scientists can now benefit from its integrated, effective, efficient, and more streamlined analytics environment. This book gives you foundational knowledge and insights to help you understand SQL Server 2017 Machine Learning Services with R. First and foremost, the book provides practical examples on how to implement, use, and understand SQL Server and R integration in corporate environments, and also provides explanations and underlying motivations. It covers installing Machine Learning Services;maintaining, deploying, and managing code;and monitoring your services. Delving more deeply into predictive modeling and the RevoScaleR package, this book also provides insights into operationalizing code and exploring and visualizing data. To complete the journey, this book covers the new features in SQL Server 2017 and how they are compatible with R, amplifying their combined power.
Table of Contents (12 chapters)

Data exploration and data munging

Data munging in R can be done independently without using SQL Server. The following diagram illustrates a recommended high-level process that developers can follow when using SQL Server and R. If you have worked in R before, you are likely familiar with steps 2, 3, and 5 performed in R directly.

Please note that Steps 3 and 4 are optional and will be discussed more in Chapter 6, Predictive Modeling and Chapter 7, Operationalizing R Code:

Figure 4.2 - High-Level Development Process for SQL Server Machine Learning Services with R

Let's get started with Data Munging in R. Specifically, in this section, we will be working with the R environment so that we know how it works in R before we stitch it together with T-SQL. If you are familiar with R, you may skip this section. Following are prerequisites for this section:

  1. An R IDE, for example RTVS...