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UID:pretalx-europython-2023-VFLKKR@programme.europython.eu
DTSTART;TZID=CET:20230721T160500
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DESCRIPTION:There has been a renaissance around Artificial Intelligence sys
 tems in recent years. However\, despite the hype\, only a small percentage
 \, i.e. 13% of Machine Learning models see the light of day!\nWell\, effec
 tively building and deploying machine learning models is more of an art th
 an science! ML models are indeed inherently complex\, have fuzzy boundarie
 s\, and rely heavily on data distribution. But what if they are trained on
  biased data? Then they’ll generate highly biased decisions! As the famo
 us saying goes by\,  “Garbage in\, garbage out\,” so if the model is t
 rained on skewed and unfair data distribution\, they are bound to produce 
 fuzzy output!\nSo\, join me in this talk as I will share my learnings in d
 eveloping effective practices to build and deploy ethical\, fair and unbia
 sed machine learning models into production.
DTSTAMP:20260513T160257Z
LOCATION:Terrace 2B
SUMMARY:Building and Deploying Fair and Unbiased ML Systems : An Art\, Not 
 Science - Rashmi Nagpal
URL:https://programme.europython.eu/europython-2023/talk/VFLKKR/
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