Microsoft, at the Strata conference, has announced that the Azure Machine Learning service for big data in the cloud is now available for use. Also, other announcements were made pertaining to enhancements of the platform, given that its Beta was released in June 2014.
Joseph Sirosh, vice president at Microsoft, and in charge of Azure ML, spoke of one substantial change, in saying, “We have added Python, which is a big favorite of data scientists. There is a huge ecosystem for this. We made a lot of improvements and adding Python was part of that. Azure Machine Learning is the platform. You can copy a bit of Python code and plug it into the studio and create an API.”
Also, the platform now also supports Spark and Hadoop, which offers a number of tools for its users to process big data, no matter what platform you choose.
Yet the real advantage of using this platform lies in its ability to create APIs quickly while also processing data very quickly.
What also took months for developers to build has been made very simple and efficient by the cloud, considering that it only takes a few hours for IT professionals to build an application once the data set was identified by data scientists.
In fact, APIs can be built just by a few clicks where applications can use either R or Python code or a combination of both, pointing to an amazing range of choices being offered as a result.
And while IBM and SAS also offer a similar set of services, the integrated approach that Azure Machine Learning has on offer is definitely one-of-a-kind.