CME 465

Embedded Machine Learning

Lec 01 and Lab L01 selected

This course provides an overview of machine learning systems, leading to practical implementation and application for embedded hardware devices. Topics include supervised and unsupervised learning systems, performance evaluation metrics, feature engineering, dimensionality reduction, data fusion and hardware implementation. The students will implement, test and analyze a machine learning systems using both software and hardware techniques.

Sections

Lecture
Lab

Syllabus

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