SQL Server 2017 Machine Learning services with R book

By tomaztsql


(This article was first published on R – TomazTsql, and kindly contributed to R-bloggers)

Yes, I am finally blogging this.

This blog post is slighty different, since it brings you the tittle of the book, that my dear friend Julie Koesmarno (blog | twitter) and I have written in and it was published in March 2018 at Packt Publishing.


Book covers the aspect of the R Machine Learning services available in Microsoft SQL Server 2017 (and 2016), how to start, handle and operationalise R code, deploy and manage your predictive models and how to bring the complete solution to your enterprise environment. Exploring the CD/CI, diving into examples supporting RevoScaleR algorithms, bringing closer the data science to database administrators and data analysts.

More specifically, content of the book is following (as noted in table of content):

1: Introduction to R and SQL Server
2: Overview of Microsoft Machine Learning Server and SQL Server
3: Managing Machine Learning Services for SQL Server 2017 and R
4: Data Exploration and Data Visualization
5: RevoScaleR Package
6: Predictive Modeling
7: Operationalizing R Code
8: Deploying, Managing, and Monitoring Database Solutions containing R Code
9: Machine Learning Services with R for DBAs
10: R and SQL Server 2016/2017 Features Extended

My dear friend, co-author and long time SQL Server community dedicated tech and data science lover, Julie and myself, we had great time working on this book, sharing the code, the ideas and collaborating on what was the great end product. Thank you, Julie.

I would also like to thank all the people involved, with their help, expertise, inspirations, people at the Packt Publishing, to Hamish Watson and also a special thanks, to you, Marlon Ribunal (blog | twitter), for your reviews and comments in the time of the writing and your review and to you, dear David Wentzel (website| linkedin ) for your chapter comments and your review.

Finally, thank you Microsoft SQL Server community, SQL friends and SQL family, R community and R Consortium, and the Revolution Analytics community, gather and led by David Smith (twitter). Not only did this concept of R in Microsoft SQL Server, but also the intersection of technologies brought together so many beautiful people, minds and ideas, that will in future time help so many business and industries world-wide.

Much appreciated!

Book is available on Amazon or you can get your copy at the Packt.

Happy reading and coding!

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