Senior year CS undergraduate at BITS Pilani - Pilani campus India. As a JSOC '20 student I worked on Fairness.jl . I am interested in fairness in machine learning, causality, counterfactual fairness and reinforcement learning. Lately, I have been exploring Quantum AI and causal RL. Happy to chat at email@example.com or julia slack :-)
To know more about me, visit www.ashrya.in
This talk introduces Fairness.jl, a toolkit to audit and mitigate bias in ML decision support tools. We shall introduce the problem of fairness in ML systems, its sources, significance and challenges. Then we will demonstrate Fairness.jl structure and workflow.