Machine Learning for Engineers.
Faculty of EngineeringDepartment of Electrical and Computer Engineering
Description
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.
Course outline
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