Successes, Failures and Learning From Them
published: Aug. 16, 2007, recorded: August 2007, views: 5609
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Another topic of interest here is to highlight some of the classic mistakes made in the field. Topics of interest here could range from the use of non-representative training data to the ignorance of population drift when modeling time-varying data, from not accounting for errors in data or labels in the model to an over reliance on a single technique for the task on hand and from asking the wrong question in the context of the application driver to sampling without care. A related topic here might be to think about the role of benchmark datasets and algorithms, and reflect on the general importance and requirement for repeatable and reproducible results.
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