Applied Machine Learning

Host University

George Mason University

Semester

Spring 2025

Course Number

AIT 736 DL1

Credits

3

Instructor

Marasco, Emanuela (emarasco@gmu.edu)

Times and Days

Asynchronous

Course Information

Machine learning as a field is now incredibly pervasive with several applications such as homeland security face recognition, self-driving car, social media, bioinformatics, etc. This course provides a broad introduction to machine learning, deep learning, and statistical pattern recognition. It introduces interdisciplinary machine learning techniques such as statistics, linear algebra, optimization, and computer science to create automated systems able to make predictions or decisions without human intervention. This class will familiarize students with a broad cross-section of models and algorithms for machine learning, and prepare students for research or industry application of machine learning techniques. The course also provides students with opportunities to gain hands-on experience with several machine learning tools.Offered by Info Sciences & Technology. May not be repeated for credit.

Prerequisites

Basic knowledge of probability theory, statistics, linear algebra and programming.