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Interpretable machine learning applications: Part 5
Completed by Luke Gardner
September 20, 2024
1 hours (approximately)
Luke Gardner's account is verified. Coursera certifies their successful completion of Interpretable machine learning applications: Part 5
What you will learn
 Be acquainted with the basics of the Aequitas Tool as a tool to measure and detect bias in the outcome of a machine learning prediction model.
Learn more about a real world case study, i.e., predictions of recidivism (COMPAS dataset), and how the prediction model may have been biased.
Learn a technique, which is largely based on statistical descriptors, for measuring bias and fairness for Machine Learning (ML) prediction models.
Skills you will gain
