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.
| Pages : | 233 pages |
| Size : | |
| Downloads: | 10 |
| Created: | 2020-08-29 |
| License: | CC BY 4.0 |
| Author(s): | Jurgen Beyerer (Editor), Christian Kuhnert (Editor), Oliver Niggemann (Editor) |
Warning: Trying to access array offset on false in /home/tutovnfz/public_html/amp/article-amp.php on line 263
Others related eBooks about Machine Learning for Cyber Physical Systems
TensorFlow, Google's library for large-scale machine learning, simplifies often-complex computations by representing them as graphs and efficiently mapping parts of the graphs to machines in a cluster or to the processors of a single machine.
Everything you really need to know in Machine Learning in a hundred pages!
Download free course Understanding Machine Learning, pdf file on 449 pages by Shai Shalev-Shwartz, Shai Ben-David.
This book explains to you how to make (supervised) machine learning models interpretable.
Download Understanding Machine Learning tutorial, a complete eBook created by Shai Shalev-Shwartz and Shai Ben-David.