Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

YouTube

Auditing Black-box Models

Association for Computing Machinery (ACM) via YouTube

Overview

Explore a hands-on tutorial from the FAT* 2018 conference that delves into auditing black-box models. Learn techniques to interpret complex machine learning models with multiple inputs and parameters. Discover how to identify potential indirect dependencies on protected attributes and assess the importance of various input factors. Follow along with the presenters as they guide you through a series of simple examples using a Jupyter notebook and their custom software library. Gain insights into the current capabilities and limitations of this auditing method, and understand how to apply it to your own datasets. This 57-minute session, led by experts from the University of Arizona, University of Utah, and Haverford College, equips you with practical skills to enhance model transparency and fairness in your machine learning projects.

Syllabus

FAT* 2018 Hands-on Tutorial: Auditing Black-box Models

Taught by

ACM FAccT Conference

Reviews

Start your review of Auditing Black-box Models

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.