Machine Learning Models Workshop I: Methods For Detecting & Correcting Bias

The first in a series of two workshops on Bias in machine learning models focused on methods for detecting and correcting bias.

The workshop covers an introduction to the topic, the importance of fairness, the definition of algorithmic fairness, and provides cases using python examples for detecting/measuring biasness and removing/reducing biasness.