K-Means clustering (using Scikit-Learn)
In this video, I tried to implement K-Means clustering using Scikit-Learn. K-Means clustering is a centroid-based clustering algorithm and is used heavily in data science. K-Means tries to minimize the within-cluster sum of squared error (WSSE) to best separate the samples within the dataset. Actually, the mean of each cluster represents the centroids.
GitHub address: https://github.com/randomaccess2023/M...
For more details, check Scikit-Learn documentation: https://scikit-learn.org/stable/modul...
45:35 Import the required libraries
02:06 Create data
03:47 Visualize data
06:12 Perform preprocessing
06:47 Perform K-Means clustering
08:51 Comparison of predictions with targets
12:08 Elbow plot to determine the best set of clusters
16:25 Check Silhouette score to determine the optimal number of clusters
#datascience #clustering #python #jupyternotebook #unsupervisedlearning #kmeansclustering #centroidbasedclustering #sklearn #matplotlib