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NOTE: Course information changes frequently, including Methods of Instruction. Please revisit these pages periodically for the most recent and up-to-date course information.


Spring 2021 Statistics GR5241 section 003
STATISTICAL MACHINE LEARNING
STATISTICAL MACHINE LEARN

Call Number 13203
Day & Time
Location
MW 8:40am-9:55am
303 Hamilton Hall
Day & Time
Location
F 2:40pm-5:25pm
417 International Affairs Building
Points 3
Grading Mode Standard
Approvals Required None
Instructor Gabriel Young
Type LECTURE
Method of Instruction Hybrid
Course Description Prerequisites: STAT GR5206 or the equivalent. The course will provide an introduction to Machine Learning and its core models and algorithms. The aim of the course is to provide students of statistics with detailed knowledge of how Machine Learning methods work and how statistical models can be brought to bear in computer systems - not only to analyze large data sets, but to let computers perform tasks that traditional methods of computer science are unable to address. Examples range from speech recognition and text analysis through bioinformatics and medical diagnosis. This course provides a first introduction to the statistical methods and mathematical concepts which make such technologies possible.
Web Site Vergil
Department Statistics
Enrollment 27 students (86 max) as of 4:52PM Saturday, December 4, 2021
Subject Statistics
Number GR5241
Section 003
Division Interfaculty
Open To GSAS
Campus Morningside
Note STAT MA students only
Section key 20211STAT5241W003

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SIS update 12/04/21 16:52    web update 12/04/21 17:20