A Rendez-Vous in Data Science

Machine Learning meets Statistics

The talk covers several typical challenges from “Data Science” arising in research projects at the Software Competence Center Hagenberg (SCCH). Classical statistics as well as modern complex machine learning methods, such as neural networks, are applied to real-world use cases from industry.

In the first part, a short presentation of SCCH as an institution for applied research is given, which is particularly interesting for students with an interest in a master or PhD thesis on practical problems.

The second part is a summary of various projects involving real-world data with a focus on recurring statistical problems from manufacturing scenarios. In particular, methods related to anomaly detection, diagnosis and prediction using machine learning methods are discussed with some care given to the black-box stigma of typical
modern machine learning methods. The presentation is intended to identify classical methods and open research questions from statistics relevant for approaches taken by SCCH’s strategy on predictive maintenance.

More information regarding the talk could be found here.

12th of March, 15:30 - 17:00, JKU Linz, Science Park 2.

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