Machine Learning on Embedded Systems
Course Description
This is a project-based class where students will learn how to develop machine learning models for execution in resource constrained environments such as embedded systems. In this class students will learn about techniques to optimize machine learning models and deploy them on a device such as a Arduino, Raspberry PI, Jetson, or Edge TPUs. The class has a significant project component.
EE 292D
Units: 3
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Typically Offered
Not Available
Grading Basis
Letter (ABCD/NP)
Class Level
Graduate
Instructional Mode
In Person
Gen Ed Requirement(s)
None
