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What Spark MLlib Does for Machine Learning

By   /  February 12, 2016  /  Data Daily | Data News, Data Education, Education Resources For Use & Management of Data, Smart Data News, Smart Data News, Articles, & Education  /  No Comments

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by Angela Guess Joseph Bradley, Xiangrui Meng, and Danny Lee recently wrote in InfoWorld, “As organizations amass greater volumes and greater varieties of data, data scientists are spending a majority of their time supporting their infrastructure instead of building the models to solve their data problems. To help solve this problem, Spark provides a general […]

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Improving Machine Learning by Reverse-Engineering a Brain

By   /  February 10, 2016  /  Data Daily | Data News, Data Education, Education Resources For Use & Management of Data, Smart Data News, Smart Data News, Articles, & Education  /  No Comments

my brains - let me show you them

by Angela Guess Derek Major reports in GCN, “Researchers are working to reverse-engineer how the brain’s visual system processes information in hopes of advancing machine learning algorithms and computer vision. The Machine Intelligence from Cortical Networks (MICrONS) research program seeks to unlock the brain’s learning methods in an effort to make computers process information more […]

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Machine Learning Takes On Long-Term Knowledge Acquisition

By   /  February 9, 2016  /  Data Articles | Data Science, Business Intelligence, & More, Data Education, Education Resources For Use & Management of Data, Smart Data Articles, Smart Data News, Articles, & Education  /  No Comments

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Learning science and Machine Learning intersect in the personalized learning layers that Cerego is powering for parties ranging from EdX MOOCs, to Arizona State University’s Global Freshman Academy courses, to publishers such as Elsevier and McGraw-Hill Education. The goal for Cerego-enhanced online learning is to help users capture knowledge – and to do it faster […]

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Microsoft Ventures Announces Machine Learning Seattle Accelerator Startups

By   /  February 9, 2016  /  Data Daily | Data News, Data Education, Education Resources For Use & Management of Data, Smart Data News, Smart Data News, Articles, & Education  /  No Comments

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by Angela Guess Taylor Soper reports in GeekWire, “Microsoft Ventures today announced its third batch of Seattle Accelerator startups that are focusing on machine learning and data science. Microsoft’s accelerator in Seattle first launched in 2014 with a cohort of home automation startups. Last year, it welcomed ‘digital work’ companies for its second batch. Now, […]

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Using Deep Learning to Read Medical Images

By   /  February 8, 2016  /  Data Daily | Data News, Data Education, Education Resources For Use & Management of Data, Smart Data News, Smart Data News, Articles, & Education  /  No Comments

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by Angela Guess A recent article in Nanalyze reports, “Let’s say you could program a deep learning algorithm to read medical images as good as doctors can. Would you then replace all your radiologists with a deep learning program? Maybe you wouldn’t, but what if that deep learning algorithm was better than your radiologists? What […]

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IBM Launches Cloud Data and Analytics Marketplace for Developers

By   /  February 5, 2016  /  Data Daily | Data News, Data Education, Education Resources For Use & Management of Data, Smart Data News, Smart Data News, Articles, & Education  /  No Comments

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by Angela Guess A new article out of the company reports, “IBM today announced a broad expansion of its Cloud Data Services portfolio with more than 25 services now available on the IBM Cloud. They are designed to help developers build, deploy and manage web and mobile applications and enable data scientists to discover hidden […]

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Image Database Visual Genome Will Help Machine Better Understand the World

By   /  January 28, 2016  /  Data Daily | Data News, Data Education, Education Resources For Use & Management of Data, Smart Data News, Smart Data News, Articles, & Education  /  No Comments

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by Angela Guess Will Knight reports in the MIT Technology Review, “A few years ago, a breakthrough in machine learning suddenly enabled computers to recognize objects shown in photographs with unprecedented—almost spooky—accuracy. The question now is whether machines can make another leap, by learning to make sense of what’s actually going on in such images. […]

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Big Data Analytics: Do Machines Have Biases?

By   /  January 26, 2016  /  Big Data Blogs, Data Blogs | Information From Enterprise Leaders, Data Education, Data Science Blogs, Data Science News, Articles, & Education, Smart Data Blogs, Smart Data News, Articles, & Education  /  No Comments

Jonathan Buckley

Click to learn more about Jonathan Buckley. The prevailing opinion is that machines and computers are cold and calculating, not prone to the same knee-jerk reactions and passions that humans tend to have. In other words, they’re unbiased. They take a certain amount of input and produce a desired result based on their programming. That […]

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2016 Trends in Data Analytics: More Hands Take Hold of the Power

By   /  January 26, 2016  /  Big Data Articles, Big Data News, Articles, & Education, Business Intelligence Articles, Business Intelligence News, Articles, & Education, Data Articles | Data Science, Business Intelligence, & More, Data Education, Education Resources For Use & Management of Data, Smart Data Articles, Smart Data News, Articles, & Education  /  No Comments

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Data Analytics is expanding its reach. In its report, Software 2016: Analytics, Acceleration and Agility, 451 Research predicts that analytics will become more prevalent throughout the layers of technology businesses use, from development to IT management, and databases to customer experience management. This is happening as the natural result of the increasing digitization of business, […]

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Machine Intelligence Supports Data Scientists

By   /  January 21, 2016  /  Data Daily | Data News, Data Education, Education Resources For Use & Management of Data, Smart Data News, Smart Data News, Articles, & Education  /  No Comments

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by Angela Guess Scott Howser recently wrote in Smart Data Collective, “Having the technology, team, and overall support in place at the onset will only help data scientists succeed and further augment results. Data scientists rely on software like machine intelligence—focused on human-interpretable results and quick iteration—to create models. If technology is outdated and/or data […]

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