2022 Fall
COMPSCI 182 001 - LEC 001
Formerly COMPSCI C182
Designing, Visualizing and Understanding Deep Neural Networks
Anant Sahai
Class #:30536
Units: 4
Instruction Mode:
In-Person Instruction
Offered through
Electrical Engineering and Computer Sciences
Current Enrollment
Total Open Seats:
74
Enrolled: 166
Waitlisted: 0
Capacity: 240
Waitlist Max: 100
Open Reserved Seats:
73 unreserved seats
1 reserved for Non-EECS Declared Engineering Majors
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.
Final Exam
TUE, DECEMBER 13TH
03:00 pm - 06:00 pm
Dwinelle 155
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 are NOT allowed for this class.
Rules & Requirements
Requisites
- Undergraduate Students: College of Engineering declared majors and L&S Computer Science
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.
Repeat Rules
Course is not repeatable for credit.
Reserved Seats
Current Enrollment
Open Reserved Seats:
73 unreserved seats
1 reserved for Non-EECS Declared Engineering Majors
Textbooks & Materials
See class syllabus or https://calstudentstore.berkeley.edu/textbooks for the most current information.
Guide to Open, Free, & Affordable Course Materials