Machine Learning
Spring 2020
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.
College: Parsons School of Design (PS)
Department: Art, Media & Technology (PSAM)
Campus: New York City (GV)
Course Format: Studio (S)
Max Enrollment: 27
Add/Drop Deadline: February 3, 2020 (Monday)
Online Withdrawal Deadline: April 12, 2020 (Sunday)
Seats Available: No
Status: Waitlist*
*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: 10:11am 12/6/2019 EST