Content: Unsupervised Learning

Project: Creating Customer Segments

In this project I applied unsupervised learning techniques on product spending data collected for customers of a wholesale distributor in Lisbon, Portugal to identify customer segments hidden in the data. I explored the data by selecting a small subset to sample and determined if any product categories highly correlate with one another. Afterwards, I preprocessed the data by scaling each product category and then identifying (and removing) unwanted outliers. With the good, clean customer spending data, I used PCA transformations to the data and implemented clustering algorithms to segment the transformed customer data.