Machine Learning by Andrew Ng at Stanford University

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source: Stanford     Last updated on 2014年9月25日
This course (CS229) -- taught by Professor Andrew Ng -- provides a broad introduction to machine learning and statistical pattern recognition. Topics include supervised learning, unsupervised learning, learning theory, reinforcement learning and adaptive control. Recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing are also discussed.

Lecture 1 | Machine Learning (Stanford) 1:08:40
Lecture 2 | Machine Learning (Stanford) 1:16:16
Lecture 3 | Machine Learning (Stanford) 1:13:14
Lecture 4 | Machine Learning (Stanford) 1:13:07
Lecture 5 | Machine Learning (Stanford) 1:15:31
Lecture 6 | Machine Learning (Stanford) 1:13:09
Lecture 7 | Machine Learning (Stanford) 1:15:45
Lecture 8 | Machine Learning (Stanford) 1:17:19
Lecture 9 | Machine Learning (Stanford) 1:14:19
Lecture 10 | Machine Learning (Stanford) 1:12:56
Lecture 11 | Machine Learning (Stanford) 1:22:19
Lecture 12 | Machine Learning (Stanford) 1:14:23
Lecture 13 | Machine Learning (Stanford) 1:14:57
Lecture 14 | Machine Learning (Stanford) 1:20:40
Lecture 15 | Machine Learning (Stanford) 1:17:18
Lecture 16 | Machine Learning (Stanford) 1:13:06
Lecture 17 | Machine Learning (Stanford) 1:17:00
Lecture 18 | Machine Learning (Stanford) 1:16:38
Lecture 19 | Machine Learning (Stanford) 1:15:55
Lecture 20 | Machine Learning (Stanford) 1:16:40