Class Description

Spring 2021

INF 385T Special Topics in Information Science : Introduction to Machine Learning

Unique ID: 28390 Danna Gurari
12:00 pm - 2:00 pm* Syllabus

DESCRIPTION

Fundamental and cutting edge concepts employed in machine learning to solve artificial intelligence problems. Theory behind a range of machine learning tools and practice applying the tools to, for example, textual data (natural language processing), visual data (computer vision), and the combination of both textual and visual data.

PREREQUISITES

Graduate standing.

Prior programming experience is strongly recommended.

SCHEDULE NOTES

Synchronous online class meetings with additional asynchronous online coursework to be arranged.

NOTE: In addition to the Monday afternoon lecture meeting, an additional mandatory online lab meeting will take place on Tuesdays 4-5pm.

RESTRICTIONS

Restricted to graduate students in the School of Information.