Event Date
SPEAKER: Paul Baines, GE Digital/Wise.io
TITLE: “Industrial Machine Learning”
ABSTRACT: From aviation to transportation to renewable energy, machine learning applications in industrial domains have the potential for dramatic impact in the field. For these industries, even small enhancements in safety and efficiency can drive substantial environmental and economic benefits. However, industrial applications of machine learning tend to be less mature and receive less attention than their consumer counterparts, despite the explosion of attention in the consumer space.
By focusing on a case study in industrial inspection analysis, this talk highlights how risk quantification and risk tolerance in industrial ML applications can differ significantly from consumer use cases. We cover some of the unique challenges and innovations required to build a robust, large-scale deep learning inspection analysis workflow, and how these differ from many of the standard challenges addressed in the literature.
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DATE: Thursday, May 30th, 4:10pm
LOCATION: MSB 1147, Colloquium Room
REFRESHMENTS: 3:30pm MSB 4110 (4th floor lounge)
STA 290 Seminar List: https://statistics.ucdavis.edu/seminars