Building and Deploying Fair and Unbiased ML Systems - An Art, Not Science
Offered By: EuroPython Conference via YouTube
Course Description
Overview
Explore effective practices for building and deploying ethical, fair, and unbiased machine learning models in production in this 30-minute conference talk from EuroPython 2023. Delve into the challenges of developing AI systems, addressing the low deployment rate of ML models, and understanding the impact of biased data on decision-making processes. Learn how to navigate the complexities of ML model boundaries and data distribution to create more responsible and effective AI solutions. Gain insights into the art of machine learning implementation and discover strategies to overcome the "garbage in, garbage out" phenomenon in AI development.
Syllabus
Building and Deploying Fair and Unbiased ML Systems: An Art, Not Science — Rashmi Nagpal
Taught by
EuroPython Conference
Related Courses
Data for Machine LearningAlberta Machine Intelligence Institute via Coursera Microsoft Future Ready: Ethics and Laws in Data and Analytics
Cloudswyft via FutureLearn AI Strategy and Governance
University of Pennsylvania via Coursera Preparar datos para la exploración
Google via Coursera Daten für die Erkundung Vorbereiten
Google via Coursera