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AI technology bursts onto the scene

When assessing the reality behind today's AI technology, businesses need to think about how it can perform in specific tasks rather than hoping for a do-it-all tool.

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Get everyone involved to build a data science team

When it comes to building a data science team, businesses should expect to find workers from a variety of backgrounds rather than holding out for a unicorn.

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Watson crams for starring analytics role

After achieving Jeopardy! success in 2011, IBM is trying to boost its Watson cognitive computing system back into the spotlight through acquisitions and by building out its Watson-based commercial products.

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Cloud services multiply machine learning options

Using the cloud for machine learning might be the best way to get the technology off the ground in some organizations.

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Business Analytics/Business Intelligence Basics

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    edge analytics

    Edge analytics applies algorithms to data at the point of collection in order to trigger actions and determine what should be sent back to a central data repository and what should be discarded.

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    AI technology bursts onto the scene

    When assessing the reality behind today's AI technology, businesses need to think about how it can perform in specific tasks rather than hoping for a do-it-all tool.

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    Tips on hiring data scientists -- and keeping them

    In a panel discussion at Strata + Hadoop World 2016, managers of data science initiatives discussed how to structure and lead teams of data scientists for effective big data analytics.

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