Algorithms inside of algorithms: Getting to fair

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Получаемые навыки

machine learning fairness, Ethics, data bias

Рецензии

4.8 (оценок: 70)

  • 5 stars
    82,85 %
  • 4 stars
    14,28 %
  • 3 stars
    2,85 %

RU

19 апр. 2022 г.

Really great discussion of algorithms and how their designs make them susceptible to bias.

SY

30 мар. 2021 г.

A relatively short and interesting course on data fairness and bias impacting AI models.

Из урока

Building fair models: theory and practice

This week we will take action against unfairness. Now that we have an understanding of fairness issues, how do we build models that do not violate them?

Преподаватели

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    Brent Summers

    Developer and Teacher

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