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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