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

Fall 2018
Unique ID: 27745
Syllabus:   Syllabus
Prof:  Gurari, Danna
Room: UTA 1.210A
Days:  Wed
Time: 3:00 pm - 6:00 pm
 

Prerequisites:
Graduate standing. Additional prerequisites may vary with the topic.

Description:
Study of the properties and behavior of information. Technology for information processing and management.

Three lecture hours a week for one semester.

May be repeated for credit when the topics vary.

This class will cover core and cutting-edge concepts employed in machine learning to solve artificial intelligence
problems. Students will learn the theory behind a range of machine learning
tools and practice applying the tools to make predictions about textual data
(natural language processing), visual data (computer vision), and the
combination of both textual and visual data. The class format is split
between reading and lab assignments for the first half of the semester
followed by a research project the second half of the semester. Each class
is split between a lecture and in-class lab tutorials.

Topic Description:
Introduction to Machine Learning

Notes:
Syllabus: https://www.ischool.utexas.edu/sites/default/files/images/webform/Syllabus-Fall2018-MachineLearning.pdf

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