What are SQL Server Machine Learning Services?

In a previous article, we have discussed about what Machine Learning is and saw some of its applications. Today, we continue this series of articles, dedicated to Data Science, Machine Learning and Artificial Intelligence (AI), by discussing what SQL Server Machine Learning Services are, and how you can use them, for efficiently implementing high-quality Data Science projects in SQL Server.


About SQL Server Machine Learning Services

SQL Server Machine Learning Services, were originally released with SQL Server 2016, known as “R Services“, with support for the R language. Later on, with the release of SQL Server 2017, one of its most significant features, was the enhanced support for Machine Learning which provided support for both R and Python programming languages. In this release of SQL Server, “R Services” were renamed to “Machine Learning Services“. In the 2019 release of SQL Server, support for the Java programming language was also added. Also, SQL Server 2019, is the first version of SQL Server that supports failover clustering for Machine Learning Services.

As defined in Wikipedia, Machine Learning is a field of computer science that gives computers the ability to learn without being explicitly programmed. Technology has matured enough, in order to finally take a deep dive into Artificial Intelligence (AI) and Machine Learning and SQL Server is no exception to that.

Read also: What is Machine Learning?

What you Can do with SQL Server Machine Learning Services

Via Machine Learning Services, you can build and deploy machine learning Solutions in R and Python via the in-database support SQL Server provides. Moreover, with Machine Learning Services you can apply powerful Data Science processing against your data and easily transform raw data into useful information and knowledge.

SQL Server Machine Learning services, provide support for the most common open source R and Python Machine Learning libraries. Also, they provide additional Machine Learning libraries created by Microsoft, that further enhance your Data Science and Machine Learning projects.

Last but not least, by using Microsoft’s free utility sqlmlutils on Github, you can install additional R and Python packages.

Read also: What is Data Science?

How can you Implement a Data Science Project?

For implementing a Data Science project using SQL Server Machine Learning Services, you need to follow the below steps:

  1. Gather the required data for your project
  2. Classify the data
  3. Create your machine learning model
  4. Train the model
  5. Run the model for generating predictions
  6. Evaluate the model for correctness
  7. Deploy the model

The above steps, are part of a Data Science project’s lifecycle, about which we talk about extensively in our online course “Introduction to SQL Server Machine Learning Services” and we show step-by-step, via a live demonstration, how you can implement a Data Science project in SQL Server, using its Machine Learning offering and Python.


Get the Course and Start Doing Data Science with SQL Server Machine Learning Services!

As already mentioned before, we are pleased to let you know that we have released a new online course related to this topic, titled “Introduction to SQL Server Machine Learning Services“.

This is an absolute beginners course, via which, you will learn what Data Science and Machine Learning are and learn how to do Data Science using the powerful SQL Server Machine Learning Services. To this end, you will learn how to execute Python and R scripts via SQL Server, as well as, how to classify data, create and train a model and finally use that model for generating predictions.

Introduction to SQL Server Machine Learning Services (MLS) - Online Course
(Enroll to the Course – Lifetime Access).

Enroll from $12.99

Enroll to the course today, get lifetime access, and get practical guides and how to’s for easily starting with Data Science and SQL Server Machine Learning Services!


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