Python for Machine Learning - The Complete Beginners Course - Implementation in Python

The video tutorial explains how to find the optimal number of clusters using the elbow method in KMeans clustering. It covers importing necessary libraries, initializing lists for WCSS values, and iterating to create clusters. The tutorial also explains the inertia method for measuring clustering effectiveness and demonstrates plotting the elbow graph to visualize the results. The video concludes with a brief mention of exploring other clustering algorithms in future lectures.

What are the steps to plot the values of clusters and inertia?

How do you interpret the results of the KMeans clustering from the plotted graph?