Course Highlights
This course features a selection of downloadable lecture notes and problem sets in the assignments section.
Course Description
This course explores the organization of synaptic connectivity as the basis of neural computation and learning. Perceptrons and dynamical theories of recurrent networks including amplifiers, attractors, and hybrid computation are covered. Additional topics include backpropagation and Hebbian learning, as well as models of perception, motor control, memory, and neural development.
Technical Requirements
*Some translations represent previous versions of courses.