It's really very helpful series. Sir, please continue this series. The placement season would start from 25 July. Please complete the playlists before 20 July.
Working on Categorical data is a tricky part but still there are approaches to calculate distance for categorical data by creating Distance Term Matrix and then Using Jaccard distance or simple matching distance methods to find out the distances for categorical data
helpful sir
Thanks Rohit.
i completed watching all ur question bank videos...amazing work...thank u so much
Thanks Swetha for your kind words. It means a lot.
Thanks much Aman..This series is so useful..Exactly what we get in interviews..I was asked about categorical data in kmeans....but i didnt expect then
Thanks for watching.
That was a great video Aman. We are waiting more videos .. :)
Very helpful...
It would really helpful Aman keep updating us 👍
I will try my best
Thank-you so much i downloaded all videos on clustering .sir also make a video on factor analysis and between difference
It's really very helpful series.
Sir, please continue this series.
The placement season would start from 25 July.
Please complete the playlists before 20 July.
Will put together as much as I can.
@@UnfoldDataScience thanks sir.
Please make video on KNN algorithm interview questions also
Working on Categorical data is a tricky part but still there are approaches to calculate distance for categorical data by creating Distance Term Matrix and then Using Jaccard distance or simple matching distance methods to find out the distances for categorical data
Ye Arvind, however of you have like more than 80% data as categories, why to process this approach just ro run k means. I m happy to be challenged.
Please do the video on kmeans ++ clustering it is a humble request sir
Sir I have watched a mock interview where you have asked what is "k" stands for, and why only "k" not l,m,n etc. Could you please answer. 🙏🏻
If over lapping occurs inbetween data than how to cluster it sir can explain in a different vedio
Ok