This half-semester course aims to introduce machine learning, a complex and quickly evolving subject deserving of a far more intensive study. The goal of this course is to open a preliminary investigation of the conceptual and technical workings of a few key machine learning models, their underlying mathematics, their application to real-world problems and their philosophical value in understanding the general phenomena of learning and experience.
Anderson, Britt. Computational Neuroscience and Cognitive Modelling: A Student's Introduction to Methods and Procedures. Los Angeles: SAGE, 2014.
Portions of the above course materials have been excerpted from Machine Learning for Designers, a text I published with O’Reilly Media, Inc. in 2016. They have been reprinted on this site with permission from the publisher.