K means Clustering Implementation | Machine Learning Project 2

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This machine learning project tutorial will look at implementing the K Means clustering algorithm on the Wine quality dataset. The elbow method and the silhouette method are used to find the optimum number of clusters. The Kelbow visualizer is also used to select the optimum value for the number of clusters.

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Roshan Cyriac Mathew

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#kmeansclustering #elbowmethod #silhouettemethod #kaggleproject #machinelearningproject

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Dear Viewers, a lot of time and effort goes into making these videos. So, all I ask of you is to subscribe to my channel (this would be at no extra cost to you!) and hit the like button if you find the video useful. This would really help my channel. Thanks in advance! - RCM.

TheAIandDSChannel

is this done under collaborative filtering
?

priyankaakhadkaa

Sir, I am developing a recommendation engine for research articles using KMeans, I got stuck while creating the recommendation function, could you help me, please

farhadkhan

From elbow method optimal no. of cluster you got was 3, but by using silhouette method you got optimal no. of clusters as 2, so why did you choose 3 clusters at the end?

kiranmahara

Hi. Do you know how to enable the option to receive recomendations while you are writting your code? I'm also using Jupyter notebook and i looked that you used it a lot while writting but i don't have those predictions.

Should i import something on jupyter for that?

joelluis

Wanna discuss about clustering Model.. how can I contact?

altafahmedmulla

I didn’t understand what is axis =1 in drop method?

sukshithshetty

Why you ignore the first high value when you did the silhouete 10:54

everydaynewchallenge

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