ECSE 551 Machine Learning for Engineers (4 credits)

Overview

Electrical Engineering : Introduction to machine learning: challenges and fundamental concepts. Supervised learning: Regression and Classification. Unsupervised learning. Curse of dimensionality: dimension reduction and feature selection. Error estimation and empirical validation. Emphasis on good methods and practices for deployment of real systems.

Terms: Fall 2020, Winter 2021

Instructors: Armanfard, Narges (Fall) Armanfard, Narges (Winter)

• Corequisite: ECSE 443 or ECSE 543 or MATH 247

• Prerequisite(s): COMP 250 and ECSE 205 or MATH 323

• Restrictions: Not Open to students who have taken COMP 551