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Course Evaluation Results

Course Details

Spring 2017-2018
* COS 485   No Pass/D/Fail

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.

Reading/Writing assignments:
Weekly problem sets.

Mid Term Exam - 30%
Final Exam - 40%
Class/Precept Participation - 5%
Problem set(s) - 25%

Other Requirements:
Statistical, design or other software use required

Prerequisites and Restrictions:
Familiarity with linear algebra, multivariate calculus, and probability theory. Knowledge of Python recommended..

Other information:
This course will count as "applications" track course.


Schedule/Classroom assignment:

Class numberSectionTimeDaysRoomEnrollmentStatus
43369 L01 03:00:00 pm - 04:20:00 pm T Th   Friend Center   101   Enrolled:71 Limit:100
43370 P01 09:00:00 am - 09:50:00 am F   Friend Center   009   Enrolled:15 Limit:25
43371 P02 03:30:00 pm - 04:20:00 pm M   Friend Center   009   Enrolled:17 Limit:25
44126 P03 09:00:00 am - 09:50:00 am F   Friend Center   108   Enrolled:18 Limit:25
44222 P04 07:30:00 pm - 08:20:00 pm M   Friend Center   003   Enrolled:21 Limit:25