Spring 2024 Statistics GR5241 section 001

STATISTICAL MACHINE LEARNING

STATISTICAL MACHINE LEARN

Call Number 13650
Day & Time
Location
F 6:10pm-8:40pm
717 Hamilton Hall
Points 3
Grading Mode Standard
Approvals Required None
Instructor Parijat Dube
Type LECTURE
Method of Instruction In-Person
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 60 students (86 max) as of 10:04AM Wednesday, December 4, 2024
Subject Statistics
Number GR5241
Section 001
Division Interfaculty
Open To GSAS
Section key 20241STAT5241W001