EECS 276: Machine Learning
Survey of techniques for the development and analysis of software that learns from experience. An introduction to computational learning theory. Bayesian approaches to learning. Instance-based methods and case-based learning. Decision tree learning. Inductive logic. Artificial neural networks. Kernel methods. Reinforcement learning. Learning from demonstrations and explicit instruction.
Repeatable for Credit: No
Normal Letter Grade only
Requisites and Restrictions
Instructor Permission Required: Yes
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