How to avoid bias in Machine Learning

Machine learning algorithms can have a big blindspot: bias. But where does it come from?
In today’s video in my Code to Care series, I’m exploring the three primary areas of the AI process to look for bias - the data, the model, and the net effect of deploying an AI model. I also cover some relatively famous examples of bias within these three areas.
Bias is a big risk in AI, so I’m exploring where this bias comes from and what you need to evaluate before deploying a new ML model.
If you have any specific questions, drop them in the comments. I’m enjoying your input and I would love to hear from you.
#AI #artificialintelligence #ML #machinelearning #CodetoCare
Check out my LinkedIn: / donwoodlock
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[@peterbedford2610]

I really like your "use cases" examples. Thanks

[@MichaelRuddock]

These videos are excellent, and so clearly explained. thank you very much.

[@siddharthvj1]

nice