Spring 2023
COMPSCI 282A 001 - LEC 001
Designing, Visualizing and Understanding Deep Neural Networks
Anant Sahai
Class #:25028
Units: 4
Instruction Mode:
In-Person Instruction
Time Conflict Enrollment Allowed
Offered through
Electrical Engineering and Computer Sciences
Current Enrollment
Total Open Seats:
63
Enrolled: 44
Waitlisted: 0
Capacity: 107
Waitlist Max: 150
Open Reserved Seats:
5 reserved for Electrical Engineering and Computer Sciences - Master of Engineering Students
6 reserved for Computer Science and Electrical Engineering and Computer Sciences Graduate Students
Hours & Workload
3 hours of instructor presentation of course materials per week, 8 hours of outside work hours per week, and 1 hours of the exchange of opinions or questions on course material per week.
Final Exam
MON, MAY 8TH
07:00 pm - 10:00 pm
Pimentel 1
Other classes by Anant Sahai
Course Catalog Description
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
Requisites
- Graduate students NOT in the Master of Engineering Program other those in EECS
Repeat Rules
Course is not repeatable for credit.
Reserved Seats
Current Enrollment
Open Reserved Seats:
Textbooks & Materials
See class syllabus or https://calstudentstore.berkeley.edu/textbooks for the most current information.
Guide to Open, Free, & Affordable Course Materials