2023 Fall
COMPSCI 282A 001 - LEC 001
Designing, Visualizing and Understanding Deep Neural Networks
Anant Sahai
Class #:26018
Units: 4
Instruction Mode:
In-Person Instruction
Offered through
Electrical Engineering and Computer Sciences
Current Enrollment
Total Open Seats:
5
Enrolled: 31
Waitlisted: 0
Capacity: 36
Waitlist Max: 150
No Reserved Seats
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
THU, DECEMBER 14TH
03:00 pm - 06:00 pm
Genetics & Plant Bio 100
Morgan 101
Physics Building 2
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.
Class Notes
* Time conflicts NOT allowed
* Non-EECS MEng students need to work with their EECS program manager if they want an exception to enroll.
* Non-EECS graduate students will remain on the waitlist until the adjustment period when the reserve caps end.
* Non-EECS MEng students need to work with their EECS program manager if they want an exception to enroll.
* Non-EECS graduate students will remain on the waitlist until the adjustment period when the reserve caps end.
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
No 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