While approaches and capabilities differ, all of these databases allow you to build machine learning models right where your data resides.

Leveraging SQL Server Machine Learning Services (R and Python) for Data Insights SQL Server Machine Learning Services (MLS) has enabled Nithin to run advanced analytics directly within the database.

But it was SQL Server’s new machine learning tools that grabbed my attention. Machine learning remains one of Microsoft’s big themes for 2017, and it’s an important segment of SQL Server 2017.

Over a month after SQL Server 2019 became generally available, Microsoft has now shined light on some more aspects of the improved machine learning capabilities offered with this release.

Consider the database’s ability to handle large datasets, support for various data types, and in-database machine learning capabilities. Ensure data quality: Data quality is critical for ...

These fully managed cloud-native smart data services empower developers to build cloud-native database and machine learning (ML) applications in SQL environments with ease.

If you're into data and databases and you have not heard the term 'machine learning,' may I suggest that you're not reading enough? This technology is hot and hyped, largely because it is the secret ...

Besides R Server 9.0, Microsoft announced the release of R Client 3.3.2, which is a slimmed down version of the main software that’s able to run on desktop personal computers, rather than servers.

Fivetran Extends Integration With Databricks, Accelerating SQL Analytics, Data Science and Machine-Learning Applications November 12, 2020 06:00 AM Eastern Standard Time ...

BERKELEY, Calif., Oct. 12, 2020 — MindsDB, the open source AI layer for existing databases, today announced their official integration with the widely used open source relational database, MariaDB ...