BIOINF 580 - Introduction to Signal Processing and Machine Learning in Biomedical Sciences
Section: 001
Term: WN 2018
Subject: Bioinformatics and Computational Biology (BIOINF)
Department: MED Bioinformatics
Credits:
3 (Non-LSA credit).
Requirements & Distribution:
BS
Consent:
With permission of instructor.
Enforced Prerequisites:
Calculus II; (B>)
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:

The course covers signal processing and machine learning methods with an emphasis on their application in healthcare. Students will need a basic understanding in linear algebra for this course. Topics include: 1) transforms and feature entraction - Fourier transform, wavelet transformation, fundamentals of information in theory. 2) Introduction to machine learning - clustering vs classification, Naive Bays, Classification and regression trees. Random forest, support vector machines, introduction to neural networks, and sparse learning. 3) applications in medicine and biology.

BIOINF 580 - Introduction to Signal Processing and Machine Learning in Biomedical Sciences
Schedule Listing
001 (LEC)
P
31824
Open
30
 
-
WF 8:30AM - 10:00AM
Note: lab meets bi-weekly beginning 2nd week of term. entry to Furstenberg is next to Med. Sci. II Bldg.
002 (LAB)
 
31825
Open
30
 
-
F 10:00AM - 11:00AM
Note: lab meets bi-weekly beginning 2nd week of term.
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