1.1 Project Background
This project is made to fulfill the project for LPS POC.
1.2 Dataset Background
The dataset used in this project is the credit card customer from a specific bank.
2.1 Objective
In this notebook the writer will try to do customer segmentation.
2.2 Project Objective Detail Steps To obtain the objective the writer will do the task within steps as follow :
- Getting insight from the dataset / EDA.
- Creating machine learning model and test it to our dataset to makes clustering of dataset.
- Creating model evaluation and model improvement.
- Drawing conclusion from overall milestone project.
2.3 Notebook Disclaimer
- The writer will mention title/explanation first, then later write the code.
- The title means to explain what writer did or tried to do with the code or to explain the output of the code itself.
- We could use these following model to cluster the customer : KMeans, Spectral Clustering, Gaussian Mixture.
- Based on this project respect to the dataset used, writer concluded ones could take consideration to use KMeans and Spectral Clustering to do segmentation.
- Three (3) clusters are the optimum number of cluster for the segentation respect to the dataset.