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CSCI 5521 - Machine Learning Fundamentals

Description
Problems of pattern recognition, feature selection, measurement techniques. Statistical decision theory, nonstatistical techniques. Automatic feature selection/data clustering. Syntactic pattern recognition. Mathematical pattern recognition/artificial intelligence.Prereq: [2031 or 2033], STAT 3021, and knowledge of partial derivatives. Class Notes: This class will be offered in a completely online format. Lectures will meet remotely and asynchronously for 90 minutes each week. Discussions during lectures will meet remotely and synchronously for 60 minutes each week. Enrollment Requirements: Exclude fr or soph 5000 level courses.
Credits
3
Attributes
UNITE Distributed Learning Section
Recent Professors
Rui Kuang, Kshitij Tayal, Catherine Zhao, Nicholas Johnson, Arindam Banerjee, Daniel Boley, Qi Zhao
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Recent Semesters
Fall 2023, Spring 2023, Fall 2022, Spring 2022, Fall 2021
Usually Held
TuTh (4:00pm-5:15pm), TuTh (1:00pm-2:15pm), TuTh (9:45am-11:00am)
Class Size
50-280
Former Title
Introduction to Machine Learning