University of Minnesota
Software Engineering Center

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Essentials of Effective Machine Learning

Date of Presentation: 
Wednesday, January 16, 2019
Presented By: 
We hear about machine learning successes all the time but not nearly as much about machine learning failures. Many assume this means that failures are uncommon, but there’s plenty of less publicized evidence to the contrary. As hype gives way to reality and data science matures as a discipline, it’s past time for increased scrutiny over how machine learning is carried out effectively. In this talk, we’ll dive into the elements that set success apart from failure with particular attention to the complications and considerations necessary to make use of machine learning in real world situations.

See Scott's presentation here.