Their uses once seemed far off for companies, but with the introduction of Machine Learning-as-a-Service (MLaaS), data science is being brought to the masses. Machine learning, a branch of artificial intelligence, is the process of using self-iterating algorithms to analyse massive amounts of data by learning from the information and processing it with minimal supervision. Essentially, machines can learn from themselves through advanced algorithms data scientists create. This technology has implications across all fields, which is why financial institutions, health services, and more are all scrambling to hire skilled data scientists. Given the demand for machine learning services, MLaaS offerings have recently sprouted up to meet this need.

Machine Learning-as-a-Service (MLaaS) exists as the nexus point for some of the most promising technologies and applications of Big Data analytics. The cumulative effect is that Machine Learning-as-a-Service expands on the possibilities of Big Data analytics while making them more accessible than ever before. "These value points derive from Machine Learning's core function: enabling analytics algorithms to learn from fresh feeds of data without constant human intervention and without explicit programming." Some of the most eminent Cloud service providers (Amazon, Google, Microsoft, IBM) are offering MLaaS either independently or as part of other platforms. Twitter recently underscored the importance of Machine Learning by acquiring Whetlab, a Machine Learning startup. Perhaps the most immediate of the aforementioned ramifications of MLaaS is the fact that it enables developers to readily incorporate Machine Learning into their applications.

On Thursday, HPE announced the immediate commercial availability of HPE Haven OnDemand, a cloud platform that provides advanced machine-learning APIs, so that developers can build data-rich mobile and web applications. Colin Mahony heads up the HPE Big Data Platform, which includes products like Vertica, Idol, and Haven OnDemand. He said that some people in the enterprise don't embrace machine learning because they view it as requiring extensive understanding of both statistics and coding. And, with Haven OnDemand, they want to make it easier for people to take advantage of machine learning tools. "What we're trying to do is say here's a portfolio, initially these 60 APIs, where you can call in, in very simple protocols through these RESTful APIS, and you can leverage a lot of the really rich machine learning that we've done," Mahony said.

With Watson, IBM seemed to have a whole year's head start on the new cognitive computing wave of technologies, as seemingly the only company with a solution ready to those who want to stay ahead of the big data curve. It looks like that monopoly could be coming to an end. Hewlett Packard Enterprise has announced its own version cognitive computing offering – the company prefers the term "machine learning-as-a-service" and is meant to give developers tools to building data-rich applications. HPE Haven OnDemand is now commercially available, and is a Microsoft Azure-based cloud platform with machine learning APIs and services targeting developers, starups and enterprises. The platform is able to perform analytics on data including text, audio, image, social, web and video.