文件名称：Andrew Ng CS229 课程英文版讲义(2017)
文件大小：4.81MB
文件格式：ZIP
更新时间：2021-08-21 07:41:43
Machine Lear
Course Description This course provides a broad introduction to machine learning and statistical pattern recognition. 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. The course will also discuss recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing.
【文件预览】：
斯坦福大学机器学习课程原始讲义2017
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