Assalam o ALikum sir I am following you since my first semester. Now I am in my last semester and your method is so good that even i can't remember my subject teacher's words. Your videos have helped me a lot in 4 years. I lesson your almost all playlists a week before exam and tomorrow is my paper of Dataware house. And end of my studies. a lot of respect ofr you from PAKISTAN from start to now you are much weaker care your health
Sir wow ap bhut hi acha pdhate ho. Sir please data science ke semester subjects ki bhi playlist layeiye. Like mongodb, oracle, python libraries pytorch, sklearn, and more. Thank u sir.❤
The approach you're describing, where centroids are updated immediately after adding a row to a cluster, sounds like a form of online or incremental K-Means clustering, which differs from the traditional batch K-Means clustering algorithm.
Yess. Exactly. First we will calculate the distance of centroids with each data points. Then assign the clusters based on min value. After that we update the centroids.
A very good video but has an error (updating centroid value before completion of an iteration). Correct method can be seen here: ua-cam.com/video/KzJORp8bgqs/v-deo.html
Nope after a new datapoint is added to a cluster new centroid if that cluster has to be calculated as it has a new data point in it and thus the centroid will keep changing
In the k-means clustering algorithm, the mean value (centroid) for each cluster is recalculated iteratively. The algorithm starts with an initial assignment of points to clusters and updates the centroids based on the mean of the points in each cluster. This process is repeated until convergence, where the assignment of points to clusters and the centroids no longer change significantly.
in certain scenarios or variations of k-means, there are adaptations that involve updating the means dynamically as new data points arrive. This is more common in online or streaming clustering algorithms. If you are working with a scenario where data points are added incrementally, and you want to update cluster means after each addition, you might be looking at an online clustering approach rather than the traditional k-means algorithm.
Sir kal hi ML me eae topic college me pade ,kuch bhi nahi samaj aa raha tha ab sab clear hogaya ek baar me hi😂 thank u sir ❤❤ Sir please ml ka pura playlist complete kardijie with python implement
Sir wow ap bhut hi acha pdhate ho. Sir please data science ke semester subjects ki bhi playlist layeiye. Like mongodb, oracle, python libraries pytorch, sklearn, and more. Thank u sir.❤
Sir kya hee pdate ho ❤❤ love your voice. Mera DBMS APKI HE help se nikla h
Assalam o ALikum sir
I am following you since my first semester. Now I am in my last semester and your method is so good that even i can't remember my subject teacher's words. Your videos have helped me a lot in 4 years. I lesson your almost all playlists a week before exam and tomorrow is my paper of Dataware house. And end of my studies. a lot of respect ofr you from PAKISTAN
from start to now you are much weaker care your health
Good luck for your future
Indians , You've got a GEM . He's better teacher than I've had at university. Appreciation from PAK.
from india, he is also better than the teacher at my uni🤞
Thanks, sis yup he is really one of the best teachers in India in Computer Field
😂😂
i don't know what they teach u at ur university, they don't believe in Darwin's law of natural selection, evolution theory
@@playing_dark2553
Kal exam hai sirrr. Or Aaj aapki yaad aagyi vapas. Thank you sir pass karane ke liye
Dwm?
Finally, I understand the fundamental of clustering and centroid. Very well explained
I really like the way you teach and its really better than international teachers in my University that is in Hatfield, UK
Sir wow ap bhut hi acha pdhate ho.
Sir please data science ke semester subjects ki bhi playlist layeiye.
Like mongodb, oracle, python libraries pytorch, sklearn, and more.
Thank u sir.❤
probably the best teacher for btech
Very Nicely Explained 👍🙏
All time my favorite Sir☺
Explained very simply.
The approach you're describing, where centroids are updated immediately after adding a row to a cluster, sounds like a form of online or incremental K-Means clustering, which differs from the traditional batch K-Means clustering algorithm.
i think after one iteration we need to do more iteration for future clustering
Sir, please make a playlist Data warehouse and mining and add all this type of videos in that playlist🙏🏻
Love you❤ sir
for that subject you can watch easy engineering classes playlist. it's a good playlist.
sir,Machine learning mai jo python ki libraries use hoti hai vo bhi krwado
like streamli , yfinance
Apse bidya teacher mene aaj tk nhi dekha
maza aagay kya easily samjhaya sir ne
I think sir, first all the values should be assigned to nearby centroid then updation should be done. Kindly check it sir 🙏
Yess. Exactly. First we will calculate the distance of centroids with each data points. Then assign the clusters based on min value. After that we update the centroids.
U are correct
Answer will be same in both methods
Haaawwwww 😳
You are right
Thank you so much sir
La jawab
Cluster1= C1, C4,C7
Cluster2= C1,C3,C5,C6
Cluster2=C2, C3, C5, C6
C7 is coming in Cluster2 !! Now im confused
no way c7 comes to same cluster of c1
You're all confusing me.. mere to exams bhi hogye🥲 bht ache gaye
C7 is coming in cluster 2 ..??
Thank you sir 🙏😊
Wahhh/// easy example
kal Data Mining ka Exam he sir thank you very much
Love ❤🎉
very nice explanation
Sir Apriori algorithm pe vidio banavo
hmarey teachers tou kuch prhatey nhi, ap pr hi bharosa hai sara
tnk you sir what a explanation sir great work😍😍
Thanks
beautifully explained!!!!
As an Indian No teacher delivered leacture on this topic in classroom but IDK why it's in syllabus😢
Good job bro!
Awesome explanation sir❤❤
wow
Thanks sir,got it🙂
Best explains ❤
thank you sir G.....?
00:40
welcome welcome
nice
amazing
🐊#THANKYOU
on night before exams we see
Sir apriori algorithm pe video bna do please 😢
A very good video but has an error (updating centroid value before completion of an iteration). Correct method can be seen here: ua-cam.com/video/KzJORp8bgqs/v-deo.html
Isn't the mean value taken only after all the dataset points are placed in clusters? and not as soon as a data point is added in one of the cluster!
yeah same doubt yar
Nope after a new datapoint is added to a cluster new centroid if that cluster has to be calculated as it has a new data point in it and thus the centroid will keep changing
In the k-means clustering algorithm, the mean value (centroid) for each cluster is recalculated iteratively. The algorithm starts with an initial assignment of points to clusters and updates the centroids based on the mean of the points in each cluster. This process is repeated until convergence, where the assignment of points to clusters and the centroids no longer change significantly.
in certain scenarios or variations of k-means, there are adaptations that involve updating the means dynamically as new data points arrive. This is more common in online or streaming clustering algorithms.
If you are working with a scenario where data points are added incrementally, and you want to update cluster means after each addition, you might be looking at an online clustering approach rather than the traditional k-means algorithm.
Moye moye...
moye moye
Sir please goodman's and kruskal's gama ko bhi padha dijiye 🙏
sir! here there is maybe you are wrong the equation c calculation first write the value of (x2 and y2) then write the x and y value
❤😮
This video is 50% correct
How???
what others take 1 hr to explain, you do it in few min.
please upload more videos on various topics of ML like HMM
Sir JB K1 and K2 both will be updated then for the next instance will we take the mean from the updated centroid or the previous k1?
did u get the answer for this question?
updated one
@@saylee.mangalmurtibtech2029 yes thank you.
@@Kanukritiii thank you.
We take mean everytime from the updated centroid because we update centroid after every step.
Sir please data mining 😢😢
Sir kal hi ML me eae topic college me pade ,kuch bhi nahi samaj aa raha tha ab sab clear hogaya ek baar me hi😂 thank u sir ❤❤
Sir please ml ka pura playlist complete kardijie with python implement
Sir agar 2 clusters ke ans same ain to then kia karna hoga?
Sir ap nay 1 part ka cantroide ki mean wrong nikali hay wrong ans a raha hay 40+20/2 =55..... Agay b sara wrong hay Check it
nahi yumna Its okay , 40+30/2 he hoga kyunkay k2 centroid m C2 k sath nearest value ayi updation bhi usi k sath hogi
sir, C3 ki value aap ne C2 m kaise rakh dia(how 200 is close to C2 and 300 is not close to C2)part nahi smjh aya🤔🤔🤔
The smaller the distance, the closer the datapoint is to the cluster so keeping that in mind, we put the datapoint in it's closest cluster.
200 c1 k to zada close tha na..ya phr jo distance c2 sy find kia wo c2 ma dalna or jo c1 sy usy c1 ma???
@@mxveesh
@@tayyabasadiq6107
Cuz you look for values like 200 . So don't look for values . You should look the distance of cluster .
❤❤
sir, please use black⬛ background 🙏🙏🙏🙏🙏
Please add subtitles, some of use can't understand your language. Thanks!
please take care of your health it seems like you are getting weak physically.
This updation thing seems to be wrong
Bhai ap kamzor ho rhy hyn 😢😅
English subtitles 😢
Learn Hindi to be in superiority.
Caption language change first
Ghar jaaa@@MdJasim-xe5fz
As I am preparing for AP Assistant Professor job please give me last minute notes sir which is ugc net paper 2 syllabus
Sir what is a Samantain it is a Hindi word and I am urdu speaking
Smjh he ni aya sir. Kisi or example sy smjhao please
Let
k=3 hai tab kaise karte hai
Ans galat aaya examein 😔
Totally wrong...Bhai tera concept galat hai....thora sa pehle padh liya kro padhaane se pehle
You have taught other subjects very well, but machine learning you are just running a train, itni jaldbazi me padhaya hua hai ki kuch samjh nhi aaraha
Sir wow ap bhut hi acha pdhate ho.
Sir please data science ke semester subjects ki bhi playlist layeiye.
Like mongodb, oracle, python libraries pytorch, sklearn, and more.
Thank u sir.❤
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