A series of talks and workshops centered around machine learning, abstraction, and algorithmic subjectivity.
Organized By Blaine O’Neill and Ulysses Pascal
Supported by the Department of Design Media Arts and Department of Information Studies.
November 16-17, 2019
From the Description:
Feature Extraction is a series of talks and workshops centered around machine learning, abstraction, and algorithmic subjectivity organized by Blaine O’Neill and Ulysses Pascal, grad students in the Design Media Arts and Information Studies departments. Participants in the first Feature Extraction weekend will learn how certain machine learning models work, play with them in creative/critical ways, and contextualize them in social, cultural, and political frameworks. We will kick off the weekend Friday night at NAVEL in downtown LA with an evening panel discussion and social, followed by 1.5 days of workshops at the EDA led by Gene Kogan and Lou Cantor.
Mashinka Firunts Hakopian
Mandy Harris Williams