Elastic, the commercial company supporting the Elasticsearch stack for searchesĀ of real-time data, has added machine learning functionality to all the pieces of the Elastic stack.Unlike some other companies, Elastic isn’t claiming this addition is cure-all magic dust. Rather, it’s for performing specific analysis for explicitly defined use cases.[ Roundup: TensorFlow, Spark MLlib, Scikit-learn, MXNet, Microsoft Cognitive Toolkit, and Caffe machine learning and deep learning frameworks. | Get a digest of the day’s top tech stories in the InfoWorld Daily newsletter. ]
In a blog postĀ that went live yesterday, Elastic outlined examples of Elasticsearch’s anomaly detection in action, such as detecting changes to a performance metric or analyzing many metrics together to determine when one is out of gamut.To read this article in full or to leave a comment, please click here

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