In this notebook I will try different cluster methods to learn more about unsupervised ML techniques. A short EDA was also conducted. For this purpose the "Mall Customer Segmentation Data" is used. The notebook is currently not yet complete and will be expanded over time.

Goal: Which group/cluster should we best target with marketing measures?

You are owing a supermarket mall and through membership cards , you have some basic data about your customers like Customer ID, age, gender, annual income and spending score. Spending Score is something you assign to the customer based on your defined parameters like customer behavior and purchasing data.

Problem Statement:

You own the mall and want to understand the customers like who can be easily converge [Target Customers] so that the sense can be given to marketing team and plan the strategy accordingly.

Dataset: https://www.kaggle.com/vjchoudhary7/customer-segmentation-tutorial-in-python

• Hierarchical Clustering (Agglomerative method)
• K-means Clustering
• Mean-shift Clustering
• DBSCAN Clustering
• Gaussian Mixture Models