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How do you know if youโre exposing your team to improper bias? Black-box and interpretable methods have the capacity to create bias, unfairness, and unexpected disparities. https://t.co/DrF6aOCfzz
@kellyp1717 wow! Just read your article - congrats!
https://t.co/vGKRcTayrJ
I work with @petercbruce (co-author of Practical Statistics for Data Scientists.) New edition coming out with Python. Email me your address and Iโll send you a signed copy - [email protected]
@tierneyl@DataVizDC I had an "aha" moment last night when you said that you've been focusing in on listening. It's true that when we jump in with a comment, an important nugget can be lost. So true! Thanks for the advice! @janetdobbins
@agrobins I was sorry that I missed you and @JackLevis final presentation at PAW. Would love to chat more about your comment wrt to partnerships at WF and other institutions. Best, @janetdobbins
.@RebeccaBilbro joins us to give us context to how YellowBrick @scikit_yb was built; its popular tools; how it can assist with model explainability, the contributions she's seen from their contributors as they approach the release of YellowBrick 1.0. https://t.co/CJ4I7tHCWB