Microsoft believes that too much of the world’s Big Data is going to waste, and so it’s just launched a new intitiative to help organizations process it all, build APIs and finally make some sense out of it.

The technology, called Azure Machine Learning (ML), is a new cloud based service that can be accessed via any web browser. It’s simple to use too, featuring a drag-and-drop interface that data scientists and deveopers will instantly get to grips with. ML’s main aim is to reduce the amount of work that’s needed for organizations to deploy machine learning, said T.K. Rengarajan, corporate vice president of data platform at Microsoft, and Joseph Sirosh, corporate vice president of machine learning at Microsoft, on the company’s blog.

“In mere hours, developers and data scientists can build and deploy apps to improve customer experiences, predict and prevent system failures, enhance operational efficiencies, uncover new technical insights, or a universe of other benefits,” they wrote.

Azure ML is likely to become an important part of Microsoft’s overall cloud strategy, as it can charge a higher price for the platform than what it does for its regular infrastructure and platform services. In addition, it will help to convince customers to use the Azure platform when they need other cloud services, rather than go with a rival like Amazon Web Services or Google.

Since being launched as a preview last July, Microsoft has added support for the Python and R programming languages, in addition to several new features, added Scott Guthrie, executive vice president of the Microsoft Cloud and Enterprise group, in another blog post.

“With today’s General Availability release you can easily discover and create Web services, train/retrain your models through APIs, manage endpoints and scale Web services on a per-customer basis, and configure diagnostics for service monitoring and debugging,” said Guthrie in the blog post.

Machine learning is a term that describes how computers improve their functionality by ingesting and analyzing data. It’s a very popular technology with Microsoft developers, who’re using it to build apps that use predictive analytics, a kind of machine learning that analyzes historical data to predict future outcomes. The only problem with putting machine learning into practice is that such systems are incredibly expensive to set up in house, due to the huge amount of hardware needed and the complexity of the software involved. Which is why making it available in the cloud should encourage many enterprises to finally give it a go.

But what kinds of businesses can benefit from machine learning? Well, one area might be website recommendations, where a number of companues have already put it to use. This involves using past activity on a website to predict the types of things people might be interested in looking at.

In his blog post, Sirosh also pointed to machine learning’s potential in medicine: “Machine learning can be used to predict the probability of a patient being admitted to hospital again,” he wrote.

“The service is entirely resident in the cloud, so all businesses can connect to it and start publishing their own machine-learning applications there. Anyone with a background in statistics or engineering can start using it in day-to-day life.”

Azure Machine Learning will be available as a full service starting on April 1 (no joke), priced at $US9.99 per seat per month, $1 per hour for use of the developer environment, $2 per every compute hour, and $0.50 per every 1,000 transactions.

Watch the video to learn more.

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