ISSP 2170 MACHINE LEARNING
DescriptionMinimum Credits: 3
Maximum Credits: 3
This course will give an overview of many techniques and algorithms in machine learning, beginning with topics such as linear and logistic regression, multi-layer neural networks and ending up with more recent topics such as boosting and support vector machines. The basic ideas and intuition behind modern machine learning methods, as well as, a more formal understanding of how and why they work will be covered. Students will have an opportunity to experiment with various machine learning techniques or apply them to a selected problem or domain in the context of a term project.
Academic Career: Graduate
Course Component: Lecture
Grade Component: Grad LG/SNC Basis
Course Requirements: PLAN: Intelligent Systems (MS, PHD)
|10605 (1030)||TuTh||1:15 pm - 2:30 pm||WWPH 2700||M. Hauskrecht||LEC||AT|
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|10630 (1030)||TuTh||1:00 pm - 2:15 pm||SENSQ 5313||M. Hauskrecht||LEC||AT|