Managing risk in machine learning
O'Reilly on Data
NOVEMBER 13, 2018
There are also many important considerations that go beyond optimizing a statistical or quantitative metric. What is needed are data scientists who can interrogate the data and understand the underlying distributions, working alongside domain experts who can evaluate models holistically. Real modeling begins once in production.
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