Tag Archives: AtScale

Big Analytics Roundup (September 19, 2016)

Many thanks to Australia’s Dez Blanchfield for his contributions to this roundup. We set out to create a special “Australia/APAC” edition; however, most of the stories have a global interest: chips are chips and deep learning is deep learning wherever you live. We did find this story, profiling a Tasmanian oyster farm that uses Microsoft’s IoT hub. Well, that’s embarrassing. MapR’s

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Big Analytics Roundup (April 4, 2016)

Strata + Hadoop World sparks a number of commercial announcements: AtScale has a new release, Microsoft previews R Server on HDInsight, and IBM puts Spark on a mainframe, FWIW. We also have a nice harvest of explainers and perspectives. Slides from Strata available here. The folks at Domino Data ask: Is XGBoost 10X faster than H2O? We’ll never know the answer, since they

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Big Analytics Roundup (March 21, 2016)

Minimal hard news this week, but some interesting survey results, analysis, articles, explainers and perspectives. — On his personal blog, Will Kurt describes Bayesian reasoning in the Twilight Zone. I tried to learn Bayesian reasoning a few years ago, but it conflicted with my prior beliefs. — Stack Overflow shares results from its 2016 Developer Survey. (h/t Thomas Ott) Key bits:

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Big Analytics Roundup (March 7, 2016)

Hortonworks wins the internet this week beating the drum for its partnership with Hewlett-Packard Enterprise.  The story is down under “Commercial Announcements,” just above the story about Hortonworks’ shareholder lawsuit. Google releases a distributed version of TensorFlow, and HDP releases a new version of Dataflow.  We are reaching peak flow. IBM demonstrates its core values. Folks who fret about cloud security

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