Customer Clustering with KMeans and Elbow Method

Implementation of K-Means Clustering for Customer Segmentation | Machine Learning Project

In this video, I explain the implementation of K-Means Clustering for Customer Segmentation using Python. The project uses the Mall Customers dataset to group customers based on Annual Income and Spending Score. I also explain each part of the code step by step, including data loading, data preprocessing, the Elbow Method, applying K-Means, and visualizing customer segments.

Topics covered:
• Importing required libraries
• Loading and understanding the dataset
• Checking missing values
• Selecting features
• Elbow Method for optimal clusters
• Applying K-Means algorithm
• Customer segmentation visualization
• Explanation of cluster results

Tools & Libraries:
• Python
• Pandas
• Matplotlib
• Scikit-learn

This project is useful for beginners learning Machine Learning and clustering algorithms.

Видео Customer Clustering with KMeans and Elbow Method канала satisfie