Machine Learning video lectures, Andrew Ng of Stanford

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Machine Learning

Lecture 1: introduction,The Motivation Applications of Machine Learning

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Course Description :

Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (clustering, dimensionality reduction, kernel methods); learning theory (bias/variance tradeoffs; VC theory; large margins); reinforcement learning and adaptive control.

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