Lecture 14 | Machine Learning (Stanford)
113 هزار بار بازدید -
16 سال پیش
-
Lecture by Professor Andrew Ng
Lecture by Professor Andrew Ng for Machine Learning (CS 229) in the Stanford Computer Science department. Professor Ng continues his discussion on factor analysis and expectation-maximization steps, and continues on to discuss principal component analysis (PCA).
This course 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.
Complete Playlist for the Course:
http://www.youtube.com/view_play_list...
CS 229 Course Website:
http://www.stanford.edu/class/cs229/
Stanford University:
http://www.stanford.edu/
Stanford University Channel on YouTube:
stanford
This course 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.
Complete Playlist for the Course:
http://www.youtube.com/view_play_list...
CS 229 Course Website:
http://www.stanford.edu/class/cs229/
Stanford University:
http://www.stanford.edu/
Stanford University Channel on YouTube:
stanford
16 سال پیش
در تاریخ 1387/05/01 منتشر شده
است.
113,052
بـار بازدید شده