EECS 545 - Machine Learning
Section: 001
Term: WN 2018
Subject: Electrical Engineering and Computer Science (EECS)
Department: CoE Electrical Engineering and Computer Science
Credits:
3
Requirements & Distribution:
BS
Waitlist Capacity:
unlimited
Advisory Prerequisites:
EECS 492.
Other Course Info:
W, odd years.
BS:
This course counts toward the 60 credits of math/science required for a Bachelor of Science degree.
Repeatability:
May not be repeated for credit.
Primary Instructor:

Survey of recent research on learning in artificial intelligence systems. Topics include learning based on examples, instructions, analogy, discovery, experimentation, observation, problem-solving and explanation. The cognitive aspects of learning will also be studied.

EECS 545 - Machine Learning
Schedule Listing
001 (LEC)
P
21258
Open
10
 
-
M 5:30PM - 8:30PM
NOTE: Data maintained by department in Wolverine Access. If no textbooks are listed below, check with the department.
Syllabi are available to current LSA students. IMPORTANT: These syllabi are provided to give students a general idea about the courses, as offered by LSA departments and programs in prior academic terms. The syllabi do not necessarily reflect the assignments, sequence of course materials, and/or course expectations that the faculty and departments/programs have for these same courses in the current and/or future terms.

No Syllabi are on file for EECS 545. Click the button below to search for a different syllabus (UM login required)

Search for Syllabus
The CourseProfile (ART) system, supported by the U-M Provost’s 3rd Century Initiative through a grant to the Digital Innovation Greenhouse, provides additional information about: course enrollments; academic terms and instructors; student academic profiles (school/college, majors), and previous, concurrent, and subsequent course enrollments.

CourseProfile (ART)