StatQuest: K-means clustering

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Information StatQuest: K-means clustering

Title	:	StatQuest: K-means clustering
Lasting	:	8.31
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Views	:	1,3 jt

The first time in 5 years that i actually understood ML algorithms clearly and actually enjoy them now
Comment from : GIGI

This is brilliantly explained, thank you! It still looks somewhat similar to KNN, confusing to understand which and when to use :/
Comment from : Somish

Hi sir is k means and kneighborhood algorithms are same ?
Comment from : Beradinho Yilmaz

can anyone please explain what the need is to convert the calculated distance from the last nearest centroid to probability distribution,instead of finding the next centroid just by calculating the distance (in KMeans++)
Comment from : Madhu Varshini

Great video, but I haven't understood what you mean by variation when explaining how to pick a velue for k, could anyone explain please?
Comment from : Wast

Thanks, Great Video 👍👍
Comment from : erfan am kh

Nice explanation ❤❤❤
Comment from : Rubana hoque chowdhury

Does cluster analysis have to start with a multicollinearity test?
Comment from : Ante Achmad

One of the best and simplest explanations of K-means clustering!!
Comment from : Mohamad Suhaib Abdul Rahman

i love it
Comment from : alex zaznobin

Great explanation!brMany thanks 👍
Comment from : Abdullah Muhammad

Wow, this is K means to the other levelbrIf you have a video about the 'Distributed Hash Tables" please let me know
Comment from : Tesfaye Yimam

Isn't tsne plot a type of clustering too?
Comment from : Kartik Malladi

Excellent explanation!
Comment from : Gil R

you are Genius:)
Comment from : Aleksey

How to cluster text data
Comment from : Madhavi Bauskar

This is by far tbe best intro oftge series, short , focused and realted
Comment from : iHisam

Thank you for my lifebr- tired student studying for AI final
Comment from : whatchyagonnado

Is choosing the initial data points randomly, the best option we have? I can't help but think that random would be very inefficient
Comment from : Mars Park

great
Comment from : Jaskaran Singh

Great content and quite simplified well, thanks
Comment from : Wiza Phiri

This felt like rocket science until today!! thanks!
Comment from : Tega Obarakpor

Great video, Thank you
Comment from : Chinthaka Liyana Arachchi

you explained in 8 minutes what my prof attempted to do in 2 hrs You are the best!!!!!
Comment from : Kam Her

what do you mean by variation? do you have a video to explain it?
Comment from : Ben Lechner

Sounds like there should be an upgrade to this technique while the location of K points is random only in the first step, after that, there may be used some kind of gradient descent right?
Comment from : Igor G

This is by far the clearest explanation I’ve seen Great video!
Comment from : David J

Thank you for explaining this!
Comment from : The 1 Kid Couple

Maa saraswati ka ashirwad hai aap par 🙏
Comment from : Abhishek Bendre

you forgot talking about "Outliers"
Comment from : Bilal shawky

Loved every min of video Sir!!brJust studied a day before exam & real glad da’t I did 😌
Comment from : Rocky Etchison

what a great video
Comment from : Hashim Mahmood

the thumbnail wasn't a clickbait, its really clearly explained! thank you sir
Comment from : Mustapha Batoot

What if my numeric data is on different scales? Wouldnt that confuse the way it identifies the nearest point? Do I need to scale all my data first?
Comment from : J94

BEST EVER I CAN FIND ON INTERNET THANK YOU
Comment from : Linn Htuts WORLD

If you ever teach shell scripting you should replace the "bam" with "shabang" or #!
Comment from : Undine

Best Intro ever!
Comment from : Đạt Dương

Amazing video Thank you Loved it 🙌 At the end, for distances with 3/4 dimensions, shouldn’t those be cube root/fourth root?
Comment from : Bhavdeep

This is so wholesome, informative, and engaging all at the same time Thank you so much for this! brbrLove the intro tune btw
Comment from : Jared Cortes

Bam?!
Comment from : Tushar Jain

Great video, thank you so much Keep it up with the amazing content
Comment from : Quang Anh

amazing and clear explanation ! horrible song tho
Comment from : aymen hammami

The video was really understandable! But how do you calculate the variation?
Comment from : Neg the trainer

You are genius sir! I wish you were my teacher when I was in my graduation brThank you 💌
Comment from : DEEPAK RAWAT

GREAT video! Shame there's cringe at the beginning :D
Comment from : Povilas Marcinkevicius

Josh: Bam???brMe: Damn…that’s beautifully explained 😢
Comment from : RBG02005

Thanks for the explanation, I finally understood this method
Comment from : MicroStick69

6:32
Comment from : Rachibe Liegise

THANK YOU SOO MUCH!! Arigato gozaimus
Comment from : Kofi Jr

Could you please share the same github link for python code?
Comment from : muskan rath

I got a campus placement as a Data Scientist and as of yet I've been in the industry for 45 years I am knee deep in everything data science barring ML and AI related intensive coding because I only know the algos at a bird's eye view and my regular work doesn't entail me needing a whole lot of things But I sat down today to start from K-means and boy am I happy I found this! Such a confidence boost when you understand something really well I don't even need packages to implement this algo should there ever be a need to do so! Thank you!
Comment from : JITHU NAIR

Thank you so much!
Comment from : ///

3 minutes into the video, I got it Great video Keep up the good work
Comment from : Henry Tirla

Thank you for this video, helped me a lot! I couldn't find a video on your channel about fuzzy c-means, but do you have one? Maybe I just couldn't find it
Comment from : Jente Meijer

Hi Joshi just love the way you explain thingsI request you to upload video on fuzzy cmeans clustering as well
Comment from : mona saeed

Your videos are so good, we actually use them in AI Class in University haha We are doing the reversed Classroom method and the Prof just linked this video for K-Means and we discussed it later Of course with additional material, but usually he does his own short videos
Comment from : Mekkes

Your videos are so good! They are calm, without being boring, in the exact rythm to understand the concept without getting tired of it, and doing it so perfectly is an art Congratulations StatQuest, you got another sub!
Comment from : Portho Games BR

What if euclidean distance between a point and 2 central points equal?
Comment from : kelvin maumba

Hi Josh, do you have any video for Silhouette Method? So far all explanations I found are very poor
Comment from : Pablo Paiva

Nicely explained, "Question?" - Dwight much ? 😅
Comment from : sunil patra

Can you do a video on Block Clustering? Would love to see you do one specifically on that
Comment from : W

You won me over with the intro
Comment from : Storm Robinson

Your video is sooooo clear!!!!!!!!! Thx!
Comment from : Yibing Jiang

What a beautiful Intro Josh <3
Comment from : Hannah Bergeron

Thanks for the clearly explanation What if there are two or many same distances from centre points to other points
Comment from : Chamara jayanath

in case of the YX axis case, mean is the mean of the values of the cluster or the centre point of the cluster on the 2D axis ?
Comment from : Abdul Sami

i can understand this clearly thanks for your video
Comment from : Huy Trần

Your videos are so clear and well explained, thank you so much for this content
Comment from : Luis Talavera

AWESOME SONG BROObrStat Quest!
Comment from : Better Call Haroon

have you worked as a data scientist? if so is it as easy as this? I'm just finishing a masters
Comment from : karrde666666

Such an amazing explanation!brEnjoyed it a lotbrThanks for the video
Comment from : Parampreet Singh

BAM
Comment from : Jesse Wild Pol

I have watched so many of your videos They are sooooo helpful My understanding of ML and stats is at a new level now thank you for making them You are the best!! could you also make some videos about time series and causal inference methodologies
Comment from : Ariel Jiang

this one has my favorite statquest melody!
Comment from : Ariel Jiang

Dear Researcher, kindly guide, how can i cluster the questionnaire line items of the large data set like more than1000 observation? brI have 79 final line items of questionnaire now i want to cluster the line items into distinct latent variable kindly guide me how can i cluster the line items thanks in anticipation
Comment from : muhammad qasim

Thank you Nobody can explain this better! Just watched this one video and I hit 'Subscribe'
Comment from : Muthu

StatQuest!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
Comment from : Some Call Me, Tim

This is awesome Thanks!
Comment from : Fritschge128

Hi Josh, I guess the representation elbow plot is incorrect Since the reduction in variance (within each cluster) is indirectly proportional to no of cluster The slope must be negative rather than positive 🧐
Comment from : Amir Ali

Great explanation! thank you very much :)
Comment from : Shamanth Raj Reddy

why do almost everyone goes with k means not DBSCAN or Hierarchical ? Is there a precedence of an algorithm over other?
Comment from : Amir Ali

should we standarize features on k-means?
Comment from : Nabiila _

key-nay-e-viritz'wors-parse-ebul-taysts!!'inno
Comment from : steph clements

Thanks!
Comment from : Mehul Patel

fantastic, by the way i like your tone, it is not boring
Comment from : Mr J

very informative
Comment from : vibii

Who is watching this 1 day before the final exams?
Comment from : Gatsby Liu

Do you have an idea about assumptions in the case of large variations? Can you explain it?
Comment from : dataanalyst101

At the start of the video , Bam? After the end, ohhhhhhh BAM!!! Thanks to you, I am ready for my interview
Comment from : Hariharan Venkatesan

Thank you so much for your awesome videos!brbrCould you please make a video for Gaussian Mixture Models too?
Comment from : DEEPAK SV

THANK YOU I LOVE YOU <3
Comment from : Stella Friaisse

Do we have a video about Gaussian Mixture Models and EM on StatQuest, please
Comment from : Daisy W

Bam? 😅
Comment from : setiawan aji

You make my research almost complete Thanks for useful and clearly explanation <3
Comment from : Patipon W

Hey teacher, I follow you from Algeria I ask you to translate what you write into Arabic so that I can understand you because I do not know English 😭😭
Comment from : Widad Kouache