Course Discription |
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This course covers the fundamentals of artificial intelligence and machine learning including
supervised learning, unsupervised learning, reinforcement learning and adaptive control. The
course discusses examples including: support vector machines, generative/discriminative learning, parametric/non-parametric learning, clustering, dimensionality reduction, kernel
methods, learning theory, and neural networks. Also, the course presents recent machine
learning applications such as data mining and bioinformatics. |