Fall 2023 Statistics-Computer Science GR6701 section 001

Probabilistic Models and Machine Learnin

Prob. Models & Macine Lea

Call Number 13419
Day & Time
Location
TR 8:40am-9:55am
142 Uris Hall
Points 3
Grading Mode Standard
Approvals Required Instructor
Instructor David Blei
Type LECTURE
Method of Instruction In-Person
Course Description

Probabilistic Models and Machine Learning is a PhD-level course about how to design and use probability models. We study their mathematical properties, algorithms for computing with them, and applications to real problems. We study both the foundations and modern methods in this field. Our goals are to understand probabilistic modeling, to begin research that makes contributions to this field, and to develop good practices for building and applying probabilistic models.

Web Site Vergil
Department Statistics
Enrollment 77 students (100 max) as of 7:06PM Wednesday, May 1, 2024
Subject Statistics-Computer Science
Number GR6701
Section 001
Division Graduate School of Arts and Sciences
Open To Engineering:Graduate, GSAS
Campus Morningside
Note PhD students only.
Section key 20233STCS6701G001