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    H Machine Learning
    A larger pool of workers can now foresee anomalies in order to optimize operations.
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    Real-time data has unique traits that separate it from other types of data used in machine-learning models.
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    hero-machine-learning
    OT has lagged in utilizing machine learning to harness the full scope of data.
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    Plus: Five trends that we believe will happen in the world of QA in the next three years.

    News

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    purdue
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    "It is important to bridge the brownfield world to a new architecture leveraging open standards and broaden access to data."
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    any prediction model should first be built on first principal historical failures paired with supporting event/process data.
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    There are promising applications of dynamic scheduling, but further research is needed to scale and scope this methodology.
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    "The more that complex big-data applications migrate to the cloud, the greater the likelihood of misallocation of resources."
    Hyper4
    "Most organizations are often unable to scale and take full advantage of end-to-end automation."