Tag Archives: Sparkling Water

Big Analytics Roundup (August 8, 2016)

So, Apple acquires Turi for $200 million. Hopefully, Apple did not pay for brand equity. Bridget Botelho argues that businesses must either disrupt or be disrupted, and outlines the role of machine learning. Someone should write a book about that. Conference Announcements — Flink Forward announces the schedule for its second annual event, to be held September 12-14 in Berlin. —

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Big Analytics Roundup (December 7, 2015)

Cloudera’s expanded Spark support leads the news this week, together with a Data Science Virtual Machine from Microsoft.  Neural network devotees will be pleased to see that Keras now runs on TensorFlow. On the Databricks blog, H2O.ai’s Michal Malohlava describes Sparking Water, a Spark package that enables data scientists to build machine learning pipelines that integrate Spark and H2O functions.

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Big Analytics Roundup (November 16, 2015)

Just three main stories this week: possible trouble for a pair of analytic startups; Google releases TensorFlow to open source; and H2O delivers new capabilities at its annual meeting. In other news, the Spark team announces Release 1.5.2, a maintenance release; and the Mahout guy announces Release 0.11.1, with bug fixes and performance improvements. (h/t Hadoop Weekly) Two items of

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Big Analytics Roundup (March 9, 2015)

Here’s a roundup of interesting Big Analytics news and analysis from the past week.  Featured this week: Hortonworks, Alpine, Spark and H2O. Hortonworks Matt Asay, writing in InfoWorld, deconstructs Hortonworks’ earnings fiasco, and with it the “100% open source” business model. Alpine Data Labs VentureBeat reports a story that Alpine Data Labs claims 10X growth in user count and billings year over year.

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Software for High Performance Advanced Analytics

Strata+Hadoop World week is a good opportunity to update the list of platforms for high-performance advanced analytics.  Vendors are hustling this week to announce their latest enhancements; I’ll post updates as needed. First some definition.  The scope of this analysis includes software with the following properties: Support for supervised and unsupervised machine learning Support for distributed processing Open platform or multi-vendor

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