CSG220 Machine Learning

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Created: Wed 5 July 2006
Last modified: 

You have reached the homepage for the Northeastern University, College of Computer and Information Science, Fall 2008 session of Machine Learning, also known as 'CSG220'. CSG220 is an graduate level first course on machine learning and applications.Topics covered include decision trees, regression, linear classifiers, learning theory, boosting, support vector machine, bayesian decisions, neural networks, mixture models, collaborative filtering, feature extraction, learning theory, reinforcement learning. To take the course, students are expected to have a basic background in linear algebra, probabilities, and programming.

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New

• HW4 up, due 12/15
• links to various materials added on the syllabus page
• HW3 up, due 11/25
• HW2 is up, due on 10/22. EXTENDED TO 10/24.
• HW1 is up. Because it is up late, it is due on Friday 10/03 @6PM in 250WVH
• Please submit electronically the student information

Course Information

• Basic course information

• Office Hours

  • Mondays 5:30 - 7:30PM, WVH room 250

  • or set an appoinment via email

• Syllabus (subject to change)

Course Work

• Homeworks

• Project
• 2008 presentation schedule

Grades

• Grades computation
• See your grades