Lecture by Professor Andrew Ng for Machine Learning (CS 229) in the Stanford Computer Science department. Professor Ng delves into locally weighted regression, probabilistic interpretation and logistic regression and how it relates to 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
Duration : 1:13:14
[youtube HZ4cvaztQEs]
11 comments
Comment by gekorio on April 27, 2010 at 6:01 am
Does anyone knows …
Does anyone knows if the lecture notes are available on the internet? It would be perfect do not need to pause the video every time to take them.
Comment by gekorio on April 27, 2010 at 6:01 am
he has lol
he has lol
Comment by 1888junkteam on April 27, 2010 at 6:01 am
excellent work!
excellent work!
Comment by natapolsri on April 27, 2010 at 6:01 am
You should have a …
You should have a description that give an outline content for each lecture.
Comment by utuber420 on April 27, 2010 at 6:01 am
He shd visit …
He shd visit Pakistan to be endowed with a probabilistic semantics of 0.
Comment by Wolfnoriil on April 27, 2010 at 6:01 am
It’s called …
It’s called abstracting. We use abstraction because we humans are not capable of coping with 1000s of low level concepts at once, duh.
Comment by leonoel on April 27, 2010 at 6:01 am
HE is already doing …
HE is already doing it easy XD
Comment by david04268 on April 27, 2010 at 6:01 am
Thank you so much …
Thank you so much for sharing this great lecture!
Comment by mosaguitar on April 27, 2010 at 6:01 am
it is not working …
it is not working the video no longer avaliable
Comment by zhaoyangster on April 27, 2010 at 6:01 am
it is even harder …
it is even harder while your mind was not there ^-^
Comment by zombiekid16 on April 27, 2010 at 6:01 am
Why do you smarties …
Why do you smarties make it more harder than it actually is? use plain words its hard enough.