Fairness in Machine Learning
Save
May 1, 2024
3 minute read
Fairness in machine learning is a subfield of machine learning that focuses on developing algorithms and models that are fair and unbiased. Fairness in machine learning is important because it can help to ensure that machine learning models are not biased against certain groups of people. For example, a machine learning model that is used to predict recidivism risk may be biased against black people if it is trained on data that is not representative of the population. This could lead to black people being unfairly targeted for parole violations.
Why is Fairness in Machine Learning Important?
Read More
Find a path to becoming a Fairness in Machine Learning. Learn more at:
OpenCourser.com/topic/a3vhh1/fairness
