Published on July 22, 2008 by Stanford

Lecture by Professor Andrew Ng for Machine Learning (CS 229) in the Stanford Computer Science department. Professor Ng lectures on generative learning algorithms and Gaussian discriminative analysis and their applications in machine learning.

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:
www.youtube.com/view_play_list?p=A89DCFA6ADACE599

CS 229 Course Website:
www.stanford.edu/class/cs229/

Stanford University:

Stanford University

Stanford University Channel on YouTube:
www.youtube.com/stanford

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191 Comments on "Lecture 5 | Machine Learning (Stanford)"

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interted
8 years 2 months ago

why he uses the same covariance matrix Σ for both classes' distributions? is it a convienient simplification?

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interted
8 years 2 months ago

@ulrikplate yes there is a typo. i think it's (P(X|Y)P(Y))/P(X) in this example

interted
Guest
interted
8 years 2 months ago

@ulrikplate yes there is a typo. i think it's (P(X|Y)P(Y))/P(X) in this example

interted
Guest
interted
8 years 2 months ago

@ulrikplate yes there is a typo. i think it's (P(X|Y)P(Y))/P(X) in this example

UP
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UP
8 years 4 months ago

Isnt there a typo in the Bayes rule? Should be [P(Y|X)P(X)]/P(Y) I think…

ulrik plate
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ulrik plate
8 years 4 months ago

Isnt there a typo in the Bayes rule? Should be [P(Y|X)P(X)]/P(Y) I think…

chaththa85
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chaththa85
8 years 5 months ago

genious..its really an excellent work!…

chaththa85
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chaththa85
8 years 5 months ago

genious..its really an excellent work!…

1888junkteam
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1888junkteam
8 years 6 months ago

excellent work!

1888junkteam
Guest
1888junkteam
8 years 6 months ago

excellent work!

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