Lecture 60 - The k Means Algorithm | Stanford University

[@mariapotterf561]

awesome !!! great explanation, simply, useful, efficient ! I feel that I really understood the topic... Thank you !

[@lockercoin3693]

very helpful and easy to understand. Keep up the good work!

[@vitorribeirosa]

Thanks for your class... Well explained!!!

[@asheeshmathur]

Excellent start, cleared my initial doubts. Keep it up

[@coryhamilton]

Excellent explanation. Very concise but covered the right details.

[@malharjajoo7393]

The approach at 10:30 is implemented in Matlab as kmeans++ algorithm

[@bhargavm6412]

its helpful it you show the calculatins...

[@manalipsahota153]

Nice explanation !!! Thank you

[@kamibank]

very well done.

[@yourpenfriend]

Let's say I have a high dimensional dataset which contains 100 features. For picking the initial k points if I follow the approach 2 (dispersed) then how can I manually understand the distance as I cannot plot this high dimensional dataset in 2d graph.

[@Redwan06me]

All you need to do is to compute the euclidian distance. This video explains better kzbin.info/www/bejne/apOYlWajqrWEo6M

[@evry1loveronica]

best tutorial ever!

[@surenderbhagat9933]

Can anyone help me out how to merge cluster if they are close to each other or if they are in a particular direction

[@AScheccher]

very useful explanation .

[@OK-dy8tr]

Lucid explanation !!

[@BOUTAYEBMarouane]

hello someone can help me to resolve ? 1) Create the core functions: - polynomial (c, h, x, y) -Gaussian (standard deviation, x, y) -sigmoid (alpha, beta, x, y) -khi-two (x, y) 2) create a function that constructs a gram matrix. 3) Karnelk means classification algorithm

[@nataliahanson6070]

thank you wonderful video

[@snowsel6686]

I love this video. can you please sent me the link to the next video?

[@ArtificialIntelligenceAllinOne]

The playlist is implicitly ordered. kzbin.info/aero/PLLssT5z_DsK9JDLcT8T62VtzwyW9LNepV I will put a number in front of each video, thanks for pointing out that!!!

[@snowsel6686]

Thanks Sir. What I am really looking for is the continuation to the K-means clustering video. Could you please just put the link here because I can't seem to locate it. THanks

[@ArtificialIntelligenceAllinOne]

Here you go! kzbin.info/www/bejne/hIGUi55ugr5jbs0

[@snowsel6686]

thanks very much

[@lucailvec]

go to the stanford page not those link

[@vishnu2avv]

Nice Video :-)

[@prem14462]

nice explanation. Thank u

[@rk2119]

disappointed Stanford - it needed to show the k-means with pictures graphs diagrams - just a dry explanation is no use - hope you will use this feedback - thanks for the attempt

[@nawshadfarruque9730]

Using another clustering algorithm to pick K points seems to me like a oxymoron.

[@ayushpatro]

Why is there so much saliva?

[@johnrabi5498]

good

[@debarkasengupta4500]

what about convergence proof etc ... this is too naive

[@raviteja9298]

Relax Bro. He can only cover so much in a 13 minute video.

[@valentinstefanov489]

unfortunately useless.