Deep Learning for Predictive Quality And Predictive Maintenance
Artificial Intelligence plays a major role in Industry 4.0 and more industrial companies than ever are starting to utilize their data to gain value and insights. The industrial domain offers very promising opportunities but this potential also comes with very specific requirements and challenges.
This talk gives insights into the characteristics of Industrial AI and how state of the art deep learning methods can be applied to solve complex problems and bring more value to companies.
Simon Stiebllehner (Head of AI at craftworks and lecturer in statistics and digital marketing at Vienna University of Economics and Business and University of Applied Sciences of WKW) and Daniel Ressi (Data Scientist at craftwork) talk at Vienna Data Science Group – Knowledgefeed vol. 27.
Slides are available here:
http://bit.ly/VDSG_Kf27rev
Artificial Intelligence plays a major role in Industry 4.0 and more industrial companies than ever are starting to utilize their data to gain value and insights. The industrial domain offers very promising opportunities but this potential also comes with very specific requirements and challenges.
This talk gives insights into the characteristics of Industrial AI and how state of the art deep learning methods can be applied to solve complex problems and bring more value to companies.
Simon Stiebllehner (Head of AI at craftworks and lecturer in statistics and digital marketing at Vienna University of Economics and Business and University of Applied Sciences of WKW) and Daniel Ressi (Data Scientist at craftwork) talk at Vienna Data Science Group – Knowledgefeed vol. 27.
Slides are available here:
http://bit.ly/VDSG_Kf27rev
