Machine Learning Times
Machine Learning Times
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How Machine Learning Works for Social Good
  Originally published in KDnuggets, Nov 2020. This article...
Diversity and Collaborative Problem Solving to Address Wicked Data Ethics Problems
 The complexity of the ethical issues facing professionals who...
Climate Tech Needs Machine Learning, Says PAW Climate Conference Chair
  Straight from the horse’s mouth – the founding...
Predictive Policing: Six Ethical Predicaments
  Originally published in KDNuggets. This article is based...
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9 months ago
Industrial Asset Optimization: Connecting Machines Directly with Data Scientists

 For more from this author, attend his virtual presentation, Industrial Asset Optimization:  Machine-to-Cloud/Edge Analytics, at Predictive Analytics World for Industry 4.0, May 31-June 4, 2020.  For industrial firms to realize the benefits promised by embracing Industry 4.0, the access to clean, quality asset data must improve.  Most of a data , scientist’s work, in any vertical, involves cleaning and contextualizing data, or “data prep”.  In the industrial segment, this remains true, and, considerably more challenging. Enterprise-wide data ingest platforms tend to yield inefficient, incomplete data necessary to optimize assets at the application layer.  In order to improve this,

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