2024 Fall

DATA C182 999 - DIS 999

Formerly COMPSCI C182

Designing, Visualizing and Understanding Deep Neural Networks

Class #:34365

Units: 4

Instruction Mode: In-Person Instruction

Offered through Data Science Undergraduate Studies

Current Enrollment

Total Open Seats: 0

Enrolled: 234

Waitlisted: 0

Capacity: 234

Waitlist Max: 50

No Reserved Seats

Hours & Workload

1 hours of the exchange of opinions or questions on course material per week, 3 hours of instructor presentation of course materials per week, and 8 hours of outside work hours per week.

Deep Networks have revolutionized computer vision, language technology, robotics and control. They have growing impact in many other areas of science and engineering. They do not however, follow a closed or compact set of theoretical principles. In Yann Lecun's words they require "an interplay between intuitive insights, theoretical modeling, practical implementations, empirical studies, and scientific analyses." This course attempts to cover that ground.

Rules & Requirements

Credit Restrictions

Students will receive no credit for COMPSCI 182 after completing COMPSCI W182, or COMPSCI L182. A deficient grade in COMPSCI 182 may be removed by taking COMPSCI W182, or COMPSCI L182.