Silhouette score is the metric that can find the optimal number of clusters in your data by using KMeans algorithm for clustering. Quick remind - Kmeans is an unsupervised learning in the area of Machine learning.

Learn how to deploy an Unsupervised Machine Learning Model (K Means) and Generate Insights that will ADD VALUE to the business! Learn how to use Python to run your Machine Learning model and optimize it and then how to deploy the results in Power BI.

In this post, you will learn about the concepts of KMeans Silhouette Score in relation to assessing the quality of K-Means clusters fit on the data.

Getting started with KMeans Clustering on text data. The data used is scraped from twitter using Tweepy, a Python library for accessing the Twitter API. This post focuses on classifying tweets into 4 major categories: Economic, Social, Cultural and Health then performing KMeans cluster analysis on the groups.

Understand K means clustering in easy steps