Are you struggling to make sense of your data? Are you looking for a way to identify meaningful patterns and insights hidden in your datasets?
Look no further! In this tutorial, I'll guide you through the process of applying K Means clustering algorithm using Excel. By the end of this video, you will have a better understanding of how to group your data into clusters based on similarities, and use those clusters to gain new insights into your data.
Whether you're working with sales data, customer demographics, or any other type of dataset, K Means clustering can be a powerful tool to help you understand and analyse your data. And the best part is that you don't need to be a data scientist or have any programming experience to use it. All you need is Excel!
The Excel file:
docs.google.com/spreadsheets/...
=== Chapters ===
04:09 Overview of the Algorithm
04:52 Standardisation of variables (Z-scores)
07:38 Setting the Clusters' Centre
07:53 Euclidian Distance
10:35 Solver for distance minimization
13:20 Pivot Table and Cluster Analysis
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