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The work presents new approaches to Machine Learning for Cyber
Physical Systems, experiences and visions. It contains some
selected papers from the international Conference ML4CPS - Machine
Learning for Cyber Physical Systems, which was held in Karlsruhe,
September 29th, 2016. Cyber Physical Systems are characterized by
their ability to adapt and to learn: They analyze their environment
and, based on observations, they learn patterns, correlations and
predictive models. Typical applications are condition monitoring,
predictive maintenance, image processing and diagnosis. Machine
Learning is the key technology for these developments.
This Open Access proceedings presents new approaches to Machine
Learning for Cyber Physical Systems, experiences and visions. It
contains some selected papers from the international Conference
ML4CPS - Machine Learning for Cyber Physical Systems, which was
held in Karlsruhe, October 23-24, 2018. Cyber Physical Systems are
characterized by their ability to adapt and to learn: They analyze
their environment and, based on observations, they learn patterns,
correlations and predictive models. Typical applications are
condition monitoring, predictive maintenance, image processing and
diagnosis. Machine Learning is the key technology for these
developments.
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