Topic: Segmenting Customers via K-means Clustering: a machine learning application in online retail.
Problem statement: How can a business automatically classify customers into different segments?
Description: The project aims to develop a machine learning model to classify customers based on Turnover, Purchase Frequency and to constructively recommend improvement decision in managing inventory and price
Impact Results: Achieved an accuracy of more than 85% on the test result, Highlighted critical improvement in prioritising stock availability and managing price based on seasons and customer segmentation
Dataset size: 541909 customers'record, Complexity: Medium
Libraries: Pandas. NumPy, Matplotlib, Seaborn, Sklearn