Lecture 5 | Machine Learning (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:
http://www.youtube.com/view_play_list?p=A89DCFA6ADACE599

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

Stanford University:
http://www.stanford.edu/

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

Category:

Education

Tags:

• science
• math
• engineering
• computer
• technology
• robotics
• learning
• algorithm
• generative
• Gaussian
• discriminative
• analysis
• digression
• naive
• Bayes
• Laplace
• smoothing

[mroulias]

exceptional. I should have gone to stanford...

[waterloocompengg]

this is great work by Professor Ng!

Good Stuff!

[MultiYolgezer]

Registered for this class at a decent level U.S institution and paying tons of money but could not even get one percent of knowledge Prof Ng delivers from the class which I attend.

[xieliming87]

@keylazy that is called total probability, to calculate probability of x, you need to take possibility x occurs for both y=1 and y=0. if you only take one, then what you have is probability for x and y=1 or y=0, not probability of x (total)

[TheCrappyaccount]

These lectures are very good

[pierrelucbacon]

Around 6:15, there is a slight mistake/typo. It should be P(y=1|x) = P(x|y=1)P(y)/P(x) ie P(y) in the numerator and not P(x)

[keylazy]

Anyone knows how to prove p(x) = p(x|y=1)p(y=1) + p(x|y=0)p(y=0)? Thanks in advance.

[2osiris1503]

wow i'm having a stanford level of education at home. Thanks for posting :)

[cidie1]

Thank you very much Professor, these are very good to have and entertaining!