LLM in Machine Learning: Customer Segmentation
Utilize LLMs to unlock sophisticated client segmentation strategies, and use cutting-edge methods to enhance your clustering models.
Overview
There are several approaches to approach a customer segmentation project. In this post, I'll show you how to define clusters and analyze the results using sophisticated approaches. This article is written for data scientists and machine learning engineers who desire to advance toward senior title status by having a variety of techniques at their disposal to handle clustering issues.
You may already be familiar with Kmeans and K-Prototype.
Thought: with the innovation of LLM, can we do LLM + Kmeans or LLM + K-Prototype? would it be better?
Well, let’s see a 2D representation (PCA) of the different models created:
As you see, the LLM + Kmeans are clustering better than the traditional approaches.
How about the other traditional clustering methods such as PCA, t-SNE or MCA
