PSAM
5020

Machine Learning

Parsons School of Design: School of Art, Media, and Tech

Non-Liberal Arts
Undergraduate Course
Graduate Course
Degree Students
Machine Learning
Spring 2024
Taught By: Aaron Hill
Section: A

CRN: 3871

Credits: 3

Machine learning is the systematic study of algorithms and systems that improve their knowledge and performance with experience. Collecting and analyzing data through machine learning algorithms and models can uncover complex patterns in massive amounts to data to make more accurate predictions and to reveal coherent dimensions. In this course students will consider classification, regression, clustering, subgroup, and association models to predict and describe, using supervised and unsupervised learning methods. Special attention will be given to models and techniques that aid and support the visualization of complex data.

Open to: All University Graduate students. Some seats have been reserved for Data Visualization students.

College: Parsons School of Design (PS)

Department: School of Art, Media, and Tech (AMT)

Campus: New York City (GV)

Course Format: Studio (S)

Modality: In-Person

Max Enrollment: 15

Add/Drop Deadline: February 4, 2024 (Sunday)

Online Withdrawal Deadline: April 16, 2024 (Tuesday)

Seats Available: Yes

Status: Closed*

* Status information is updated every few minutes. The status of this course may have changed since the last update. Open seats may have restrictions that will prevent some students from registering. Updated: 12:16pm EST 2/23/2024

Meeting Info:
Days: Wednesday
Times: 12:10pm - 2:50pm
Building: Academic Entrance 63 Fifth Ave
Room: 204
Date Range: 1/24/2024 - 5/8/2024