Friday, 11th of October
11h (room R2014, 660 building) (see location
(SINTEF digital, Norway)
Machine learning in the real world
Machine learning algorithms are flexible and powerful, but the data requirements are high and rarely met by the available data. Real world data is often medium sized (relative to problem side), noisy and full of missing values. At the same time, in order to deploy machine learning in industrial settings, they must be robust, explainable and have quantified uncertainties. I will show practical examples of these challenges from our recent projects and some case-by-case solutions, but also highlight remaining issues.
All TAU seminars: here