CS 3750 Advanced Topics in Machine Learning (ISSP 3535)
The goal of the field of machine learning is to build computer systems that learn from experience and that are capable to adapt to their environments. Learning techniques and methods developed by researchers in this field have been successfully applied to a variety of learning tasks in a broad range of areas, including, for example, text classification, gene discovery, financial forecasting, credit card fraud detection, collaborative filtering, design of adaptive web agents and others.
The objective of the Advanced Machine Learning course is to expand on the material covered in the introductory Machine Learning course (CS2750), and focus on the most recent advances in the ML field such as, kernel and variational methods. The course will consist of a mix of lectures, paper presentations and discussions. Students will be evaluated based on their participation in discussions, paper presentations and projects.
Credits vary between 3 and 0 based on agreement with instructor.
Requirements and Grading
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Class No.: 30666 (1040)
Times: 11:00 am - 12:15 pm
Room: SENSQ 5313
Instructor(s): M. Hauskrecht