Tag Archives: Cloudera

ClouderaWorks

Cloudera and Hortonworks just announced a merger. You ask: how does the merger affect the machine learning marketplace? My answer: not at all. Neither Cloudera nor Hortonworks competes in machine learning. Yes, I’m aware. Cloudera and Hortonworks see themselves as part of the machine learning value chain. You can’t do machine learning without data. You need a few other things, too. But

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Forrester’s 2018 PAML “Waves”

Forrester just published two “Wave” reports for predictive analytics and machine learning. The first, covering “multi-modal” solutions, is available here for free. A second report, covering notebook-based solutions, is available here (registration required.) Forrester plans to publish a third report, covering automated machine learning vendors, in 2019. Kudos to Forrester for understanding the diversity of the data science tools market.

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Roundup 11/9/2016

Machine learning (ML) and deep learning (DL) content from the past 24 hours. Fundamentals — On the Algorithmia blog, Charlie Crawford writes an excellent introduction to deep learning. He clearly understands the relationships among ML/DL/AI, presents a good intro to neural networks and lists some of the top DL frameworks. My only criticism is that he omits Microsoft’s CNTK/Cognitive Toolkit

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Big Analytics Roundup (May 2, 2016)

Movidius ups the ante for trade show trinkets by releasing what journos describe as supercomputing, neural computing power, vision processing, deep learning, and artificial intelligence on a USB drive.  Roundup here. Last November, IBM’s Paul Zikopoulos snarked at Cloudera for not supporting SparkR. Cloudera’s Sean Owen, responding to a query in the Cloudera Community, notes that SparkR “does not work with other resource managers,” and

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Big Analytics Roundup (April 11, 2016)

Top story of the week is NVIDIA’s new DGX-1 deep learning chip; scroll down for more on that. We have three roundups from Strata + Hadoop World, Rashomon style: Alex Woodie reports six takeaways: Kafka, Spark, Hadoop, Cloud, machine learning, mainframes. Jessica Davis recalls four things: comedian Paula Poundstone, MapR, public data sets, AI. Nik Rouda recaps five things: Spark, machine learning,

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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 28, 2016)

Microsoft’s chatbot fail wins the internet this week, but the most important story is Google’s new managed service for machine learning. Also leading the week: Mesosphere’s new funding round led by Microsoft and HPE, and more funding for Domo. — Google Cloud Platform (GCP) adds the Google Cloud Machine Learning Platform to its suite of managed machine learning services, which

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