PROTEUS

Scalable online machine learning strategies for predictive analytics and real-time interactive visualization

PROTEUS will investigate and develop ready-to-use scalable online machine learning algorithms and interactive visualization techniques for real-time predictive analytics to deal with extremely large data sets and data streams. Using both the steel industry and the European Apache Flink platform as use cases, PROTEUS will contribute to the big data arena by addressing fundamental challenges around scalability and responsiveness. Trilateral will develop the benchmarks and performance metrics to evaluate the system, including gains for the steel industry use case organisation and European big data capabilities in general. PROTEUS is a three-year project that started in Dec 2015.

For more information and updates visit the PROTEUS project website and follow us on Twitter @proteus_bigdata

 

Please contact our team for more information:

Rachel Finn, Practice Manager

Rachel Finn Practice Manager

PROTEUS – Scalable online machine learning strategies for predictive analytics and real-time interactive visualization – has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 687691.

‘Risk Assessment Report and Methodology’

You can view the Executive Summary and Table of contents of the Project Solebay Risk Assessment Methodology Report.

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