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Introduction to Machine Learning - Brown University

Introduction to Machine Learning Brown University CSCI 1950-F, Spring 2012 Instructor: Erik Sudderth Graduate TAs: Dae Il Kim & Ben Swanson Head Undergraduate TA: William Allen Undergraduate TAs: Soravit Changpinyo, Zachary Kahn, Paul Kernfeld, & Vazheh Moussavi Visual Object Recognition trees skyscraper sky bell dome temple buildings sky Spam Filtering !Binary classification problem: is this e-mail spam or useful (ham)? !Noisy training data: messages previously marked as spam !Wrinkle: spammers evolve to counter filter innovations Spam Filter Express Collaborative Filtering Social Network Analysis Chang, Boyd-Graber, & Blei, KDD 2009 !Unsupervised discovery and visualization of relationships among people, companies, etc.

Introduction to Machine Learning Brown University CSCI 1950-F, Spring 2012 Instructor: Erik Sudderth Graduate TAs: Dae Il Kim & Ben Swanson ... Basic machine learning is about the last 3 steps "! More advanced methods can help learn which features are best, or decide which data to collect .

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