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This repository contains a collection of fundamental topics and techniques in machine learning. It aims to provide a comprehensive understanding of various aspects of machine learning through simplified notebooks. Each topic is covered in a separate notebook, allowing for easy exploration and learning.
This notebook is about creating a 2D dataset and using unsupervised machine learning algorithms like kmeans, kmeans++, and Agglomerative Hierarchical clustering methods to classify data points, and finally comparing the results.
Datasets for this notebook consists of credit card usage behavior of customers with 18 behavioral features. Segmentation of customers can be used to define marketing strategies.