EECS 445 - Introduction to Machine Learning
Section: 001
Term: FA 2019
Subject: Electrical Engineering and Computer Science (EECS)
Department: CoE Electrical Engineering and Computer Science
Credits:
4
Requirements & Distribution:
BS
Enforced Prerequisites:
EECS 281 and (MATH 214 or 217 or 296 or 417 or 419); (C or better; No OP/F).
Advisory Prerequisites:
MATH 214 or equivalent; STATS 250 or equivalent.
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:

Theory and implementation of state of the art machine learning algorithms for large-scale real-world applications. Topics include supervised learning (regression, classification, kernal methods, neural networks, and regularization) and unsupervised learning, (clustering, density estimation, and dimensionality and reduction).

EECS 445 - Introduction to Machine Learning
Schedule Listing
001 (LEC)
 
32499
Open
12
 
-
MW 12:00PM - 1:30PM
Note: STUDENTS ARE AUTO-ENROLLED IN LECTURE WHEN THEY ELECT A DISCUSSION. Undergrads only. Undergrads who do not meet major restrictions can request permission for this course on or after Wednesday, April 24, 2019 through the CSE Undergraduate Advising Office.
002 (LEC)
 
31690
Open
6
 
-
MW 2:00PM - 3:30PM
Note: STUDENTS ARE AUTO-ENROLLED IN LECTURE WHEN THEY ELECT A DISCUSSION. Undergrads only. Course will open to EE UG who meet course prerequisites on Friday, April 19, 2019.
011 (DIS)
P
22528
Open
1
 
-
F 11:30AM - 12:30PM
012 (DIS)
P
24349
Open
3
 
-
Th 4:30PM - 5:30PM
013 (DIS)
P
24350
Open
2
 
-
F 1:30PM - 2:30PM
014 (DIS)
P
29510
Open
2
 
-
F 12:30PM - 1:30PM
015 (DIS)
P
29511
Open
3
 
-
F 2:30PM - 3:30PM
016 (DIS)
P
29512
Open
3
 
-
Th 12:30PM - 1:30PM
017 (DIS)
P
32916
Open
4
 
-
Th 5:00PM - 6:00PM
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