Python for Machine Learning - The Complete Beginners Course - Steps of the Elbow Method

The video tutorial explains the elbow method used in K means clustering. It describes how the method identifies the optimal number of clusters by plotting the WCSS values against the number of clusters and finding the 'elbow' point in the graph. The tutorial outlines the steps involved, including executing K means clustering for different K values, calculating WCSS, and plotting the results. The sharp bend in the graph, resembling an elbow, indicates the best K value. The video concludes with an overview of the implementation steps.

What steps are involved in executing the elbow method?

Explain how the elbow method determines the best value of K.