What’s the advantage of looking at machine learning from the platform perspective? Breadth and depth, says Skytree co-founder and CEO Martin Hack. In contrast to a single point algorithm that learns about one thing really well for a particular need as it goes about analyzing more and more Big Data sets, Skytree takes the tack that there’s a whole universe of algorithms and methods that can be applied to support a variety of use cases.
The company is a startup, closing a Series A funding round this spring to the tune of $18 million. Skytree’s algorithms are available in different packages for application across industries, or even to fit different needs within the same industry or company. The six biggest machine learning use cases across industries, Hack says, are classification, regression, clustering, entity estimation, dimension reduction and multidimensional querying, and those six tasks, individually or in combination, provide the foundation for performing advanced analytics such as outlier detection or value prediction, among others, that are applicable to various scenarios. “Outlier detection could be used in trying to detect fraud or to find terrorists,” he says. “It’s virtually the same platform. The data changes and the output changes, but the computation part is the same.”