Thursday, June 29, 2017

TensorFlow to Hadoop By Way of Datameer

Companies that want to use #TensorFlow to execute deep learning models on big data stored in #Hadoop may want to check out the new #SmartAI offering unveiled by #Datameer today. Deep learning has emerged as one of the hottest technique for turning massive sets of unstructured data into useful information, and Google‘s Tensorflow is arguably the most popular programming and runtime framework for enabling it. So it made sense that Datameer, which was one of the first vendors to develop a soup-to-nuts Hadoop application for big data anatlyics, has now added support for TensorFlow into its Hadoop-based application. With today’s unveiling of SmartAI, Datameer is providing a way to execute and operationalize TensorFlow models. “The objective here is to take the stuff that mad scientists are coming up with, and actually take it to the business,” Datameer’s Senior Director of Product Marketing John Morrell tells Datanami. SmartAI, which is still in technical preview, is not helping data scientists to create the models. They will still do that in their favorite coding environment. Nor is it set up to train the models. If you’re interested in learning about how that can be accomplished on Hadoop, Hortonworks has a good blog post on integrating TensorFlow assemblies into YARN. Rather, Datameer’s new app is all about solving some of the thorny “last mile” problems that organizations often encounter as they’re moving a trained TensorFlow model from the lab into production. “AI today has had some problems in terms of operationalization,” Morrell says. “When a data scientist come up with a formula using their data science tools, they just chuck it over the wall to IT guy, who then tries to turn it into code, and custom code the whole thing.”

https://www.datanami.com/2017/06/28/tensorflow-hadoop-way-datameer/

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