August 2016
Beginner to intermediate
334 pages
8h 27m
English
Now that we have covered debugging, monitoring and iterative testing of predictive models, we close with a few notes on communicating results of algorithms to a more general audience.
In this text, we frequently discuss evaluation statistics or coefficients whose interpretations are not immediately obvious, nor the difference in numerical variation for these values. What does it mean for a coefficient to be larger or smaller? What does an AUC mean in terms of customer interactions predicted? In any of these scenarios, it is useful to translate the underlying value into a business metric in explaining their significance to non-technical colleagues: for example, coefficients in a linear ...
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