Through this project, I aim to segment shopping customers into groups based on specific features such as annual income, shopping score, age, and gender. Unsupervised machine learning allows us to perform this segmentation using clustering algorithms. For this project, I employed the K-Means algorithm, utilizing the elbow method to determine the optimal number of clusters.

The primary goal is to cluster customers to help companies make better-informed decisions. These clusters will provide insights into which customer groups should be targeted more effectively.