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January 2018 |
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SkyFoundry Releases Machine Learning for SkySpark® Analytics
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RICHMOND, VA. (PRWEB) JANUARY 08, 2018 SkyFoundry (http://www.skyfoundry.com),
a leading developer of analytics software for use with equipment
systems and facilities of all types, announced today the release of
Machine Learning Tools for their SkySpark® Analytics software.
SkySpark® automatically analyzes building, energy and equipment data to
identify issues, faults and opportunities for improved performance and
operational savings. The new Machine Learning Tools provide support for
supervised learning for prediction and forecasting through
regression-based approaches, and classification using Support Vector
Machine (SVM) techniques.
“We have been working with select customers for almost a year as they
tested our new machine learning tools. Their feedback helped us
optimize the tools to make application as easy as possible. The results
have been excellent and we are excited to announce their availability
to the entire market. These tools further extend the capabilities of
SkySpark and the range of solutions our partners are delivering to
customers around the globe,” said John Petze, Principal at SkyFoundry.
SkySpark combines full programmability with an extensive library of
built-in functions allowing analytics to be custom-tailored to meet the
real-world needs of individual systems and facilities. Owners and
operators are able to utilize their specialized knowledge, in
conjunction with the deep expertise of SkyFoundry Solution Partners, to
implement data analytics that fit their unique system characteristics
and project requirements.
More information about SkyFoundry and SkySpark Analytics is available at http://www.skyfoundry.com.
Overload. There are too many processes running under this userid. Please wait a minute and try again. (fork failed)About SkyFoundry
SkyFoundry provides software solutions to create value from the data
produced by the Internet of Things. SkySpark® Analytics software is an
open, extensible platform enabling data from a wide range of sources to
be automatically collected, visualized, and analyzed, to identify
opportunities for operational improvements and cost reduction. More
information is available at http://www.skyfoundry.com.
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