YoVDO

Operational Research for Fairness, Privacy and Interpretability in Machine Learning

Offered By: GERAD Research Center via YouTube

Tags

Machine Learning Courses Privacy Courses Combinatorial Optimization Courses Fairness Courses Responsible AI Courses Interpretability Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore the intersection of fairness, privacy, and interpretability in machine learning through this 45-minute DS4DM Coffee Talk presented by Julien Ferry from LAAS-CNRS. Delve into the application of operational research and combinatorial optimization tools to develop responsible AI. Gain insights into Ferry's PhD research, which examines the interactions between these crucial aspects of ethical machine learning. Learn about the innovative use of Integer Linear Programming to create interpretable, fair, and optimal models. Discover how this approach can contribute to the advancement of responsible AI practices and the development of more ethical machine learning systems.

Syllabus

Operational Research for Fairness, Privacy and Interpretability in Machine Learning


Taught by

GERAD Research Center

Related Courses

Introduction to Artificial Intelligence
Stanford University via Udacity Natural Language Processing
Columbia University via Coursera Probabilistic Graphical Models 1: Representation
Stanford University via Coursera Computer Vision: The Fundamentals
University of California, Berkeley via Coursera Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent