Tag Archives: Alpine Chorus

The Year in Machine Learning (Part Four)

This is the fourth installment in a four-part review of 2016 in machine learning and deep learning. — Part One covered Top Trends in the field, including concerns about bias, interpretability, deep learning’s explosive growth, the democratization of supercomputing, and the emergence of cloud machine learning platforms. — Part Two surveyed significant developments in Open Source machine learning projects, such as R, Python, Spark, Flink,

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Big Analytics Roundup (May 31, 2016)

Google’s TPU announcement on May 18 continues to reverberate in the tech press. In Forbes, HPC expert Karl Freund dissects Google’s announcement, suggesting that Google is indulging in a bit of hocus-pocus to promote its managed services.  Freund believes that TPUs are actually used for inference and not for model training; in other words, they replace CPUs rather than GPUs. Read

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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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Gartner Advanced Analytics Magic Quadrant 2015

Gartner’s latest Magic Quadrant for Advanced Analytics is out; for reference, the 2014 report is here; analysis from Doug Henschen here.  Key changes from last year: Revolution Analytics moves from Visionary to Niche Alpine and Microsoft move from Niche to Visionary Oracle, Actuate and Megaputer drop out of the analysis Gartner changed its evaluation criteria this year to reflect only “native”

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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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