Â鶹AV

Vue d'ensemble

Génie électrique : 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: Automne 2024, Hiver 2025

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

• Corequisite: ECSE 343 or ECSE 543 or MATH 247

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

• Restrictions: Not open to students who have taken or are taking COMP 551.