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Course Evaluation Results

Course Details

Spring 2016-2017
* COS 495   na, npdf

Special Topics in Computer Science - Neural Networks: Theory and Applications

H. Sebastian Seung

Organization of synaptic connectivity as the basis of neural computation and learning. Multilayer perceptrons, convolutional networks, and recurrent networks. Backpropagation and Hebbian learning. Models of perception, language, memory, and neural development.


Sample reading list:
See instructor for complete list

Reading/Writing assignments:
Weekly problem sets.

Requirements/Grading:
Mid Term Exam - 30%
Final Exam - 40%
Problem set(s) - 30%

Prerequisites and Restrictions:
Prerequisites: Familiarity with linear algebra, multivariate calculus, and probability theory. Knowledge of a programming language (Python, MATLAB, or Julia recommended)..

Website:  http://www.cs.princeton.edu/courses/archive/spring17/cos495/

Schedule/Classroom assignment:

Class numberSectionTimeDaysRoomEnrollmentStatus
41410 L01 3:00 pm - 4:20 pm M W   McCosh Hall   28   Enrolled:83 Limit:100
43555 P01 7:30 pm - 8:20 pm W   Robertson Hall   016   Enrolled:21 Limit:29
43808 P02 7:30 pm - 8:20 pm Th   Friend Center   109   Enrolled:20 Limit:29
43812 P03 7:30 pm - 8:20 pm W   Friend Center   108   Enrolled:22 Limit:29
44391 P04 7:30 pm - 8:20 pm W   Friend Center   112   Enrolled:20 Limit:17 Closed