Tag Archives: Microsoft Azure

The Year in Machine Learning (Part One)

This is the first installment in a four-part review of 2016 in machine learning and deep learning. In the first post, we look back at ML/DL news organized in five high-level topic areas: Concerns about bias Interpretable models Deep learning accelerates Supercomputing goes mainstream Cloud platforms build ML/DL stacks In Part Two, we cover developments in each of the leading open

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Roundup 11/17/2016

Machine learning (ML) and deep learning (DL) content from the past 24 hours. Google Enhances Machine Learning Services Google launches a dedicated team to drive Google Cloud Machine Learning, and announces a slew of enhancements to its services: — Google Cloud Jobs API provides businesses with capabilities to find, match and recommend jobs to candidates. Currently available in a limited alpha. —

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Roundup 11/11/2016

Machine learning (ML) and deep learning (DL) content from the past 24 hours. TensorFlow @ 1 A year ago, Google released TensorFlow to open source. Since then, the company has added distributed computing features, support for iOS and a managed service in the cloud. TensorFlow is now the most popular machine learning project on GitHub, and it has the largest

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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 (September 6, 2016)

Jim Kyung-Soo Liew and Tamas Budavari of Johns Hopkins ask whether Tweet sentiments still predict the stock market. Short Version: they do, but the market has arbitraged away any advantage from trading on the information. So there you have it: the stock market is efficient with respect to fundamental information, technical information, and Tweets. Enterra’s Stephen DeAngelis celebrates the “Algorithmic

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Big Analytics Roundup (August 29, 2016)

TechCrunch reports results of a new study, which says that you really don’t need a co-founder after all. Next, they’ll be telling us we don’t need to floss. Python and R Matt Asay argues that Python is a gateway language that leads data scientists to R. (h/t Oliver Vagner). That’s oversimplified and mostly incorrect. The breadth of R’s analytics functionality tends

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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 (June 27, 2016)

We have announcements from BlueData, Databricks, and DataStax this week, plus a nice crop of explainers. Also, a bit of catch-up, something from May that I missed: Bob Hayes publishes an interesting summary of his recent survey of data scientists. Includes an infographic and slides. Thiemo Fetzer asks: did the weather affect the Brexit vote? Spoiler: he says no. Presented without

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Big Analytics Roundup (April 25, 2016)

Mesosphere wins the internet this week with its announcement that it has open sourced DC/OS, its datacenter virtualization project built around Apache Mesos. While not an “analytics” project per se, DC/OS has the potential to transform how organizations provision and deploy their analytics platforms. In a nutshell, Apache Mesos distributes workloads across physical IT resources. DC/OS adds a container orchestration platform; installation,

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