CS 2750 - MACHINE LEARNING Minimum 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: Computer Science (CS-PHD; CS-MS; CSMSBS-MS) or Computer Engineering (COEAS-PHD; COEAS-MS; COEENG-PHD; COEENG-MCO) Click here for class schedule information.
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