Machine Learning

Parsons School of Design: Art, Media & Technology

Non-Liberal Arts

Graduate Course

Degree Students

Machine Learning

Spring 2019

Taught By: Aaron Hill

Section: A

CRN: 4729

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 MS Data Visualization majors.

College: Parsons School of Design (PS)

Department: Art, Media & Technology (PSAM)

Campus: New York City (GV)

Course Format: Studio (S)

Max Enrollment: 27

Enrollment Status: Closed*

*Enrollment status information is updated every five 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: 11:01pm 6/15/2019

Meeting Info:

Days: Wednesday

Times: 12:10pm - 1:35pm

Building: Academic Entrance 63 Fifth Ave

Room: 601

Date Range: 1/23/2019 - 5/8/2019

Days: Wednesday

Times: 1:45pm - 3:10pm

Building: 6 East 16th Street

Room: 1200B

Date Range: 1/23/2019 - 5/8/2019