How to Perform KMeans Clustering Using Python

Imagine that you are a Data Scientist working for a retail company and your boss requests for the customers' segmentation into the following groups: low, average, medium, or platinum customers based on spending behavior for targeted marketing purposes and product recommendations. Knowing that there is no such historical label associated with those customers, how is it possible to categorize them? This is where clustering can help. It is an unsupervised machine-learning technique used to group unlabeled data into similar categories or clusters. This conceptual article will focus more on the K-means clustering approach, one of the many techniques in unsupervised machine learning.