Performing K-Means Clustering With Python

K-Means learning is a machine learning technique used to divide a dataset into clusters to analyze its results. This classification algorithm divides a large group of data into smaller groups to maximize the similarity between data points. We will walk through applying and analyzing the K-Means clustering algorithm on a set of data using the Python libraries: pandas, scikit-learn, and matplotlib.

Learning Objectives

Upon completion of this lab you will be able to:

• Utilize Python to prepare data for Cluster Machine Learning
• Perform K-Means Clustering on a set of data
• Plotting the outcome of the K-Means clustering

Intended Audience

This lab is intended for:

• Data engineers
• Machine learning practitioners
• Anyone interested in using Python to perform clustering

Prerequisites

You should possess:

• A basic understanding of Python
• A basic understanding of K-Means Clustering

Updates

August 19th, 2025 - Resolved issue connecting to the lab's notebook

August 8th, 2024 - Added password protection to notebook