SQL Server 2017 Machine Learning Services with R

Develop and run efficient R scripts and predictive models for SQL Server 2017

About This Book

• Learn how you can combine the power of R and SQL Server 2017 to build efficient, cost-effective data science solutions
• Leverage the capabilities of R Services to perform advanced analytics—from data exploration to predictive modeling
• A quick primer with practical examples to help you get up- and- running with SQL Server 2017 Machine Learning Services with R, as part of database solutions with continuous integration / continuous delivery.

Who This Book Is For

This book is for data analysts, data scientists, and database administrators with some or no experience in R but who are eager to easily deliver practical data science solutions in their day-to-day work (or future projects) using SQL Server.

What You Will Learn

• Get an overview of SQL Server 2017 Machine Learning Services with R
• Manage SQL Server Machine Learning Services from installation to configuration and maintenance
• Handle and operationalize R code
• Explore RevoScaleR R algorithms and create predictive models
• Deploy, manage, and monitor database solutions with R
• Extend R with SQL Server 2017 features
• Explore the power of R for database administrators

In Detail

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.

Style and approach

This fast-paced guide will help data scientists and DBAs implement all new data science projects using SQL Server 2017 Machine Learning Services.