This project explores customer segmentation using various clustering techniques on a dataset of mall customers. The goal is to identify distinct customer groups based on demographic and behavioral attributes, enabling businesses to tailor their marketing strategies more effectively.

This Human Activity Recogisition analyses human activity patterns using smartphone sensor data from the UCI Human Activity Recognition dataset. It involves outlier detection, correlation analysis, and structural graph analysis. DBSCAN clustering is applied, followed by LDA for dimensionality reduction, to visualise and interpret activity clusters

Implementation of an ML algorithm, DBSCAN, on biological data.

An obstacle tracking ROS package for detecting obstacles using 2D LiDAR scan using an Extended object tracking algorithm

DBSCAN in Python

Clustering Visualizer is a Web Application for visualizing popular Machine Learning Clustering Algorithms (K-Means, DBSCAN, Mean Shift, etc.).

The main objective of this project is to group customers with similar behavior and characteristics into segments to better understand their needs and preferences. The unsupervised machine learning techniques used in this project include K-means clustering ,hierarchical clustering and DBScan Clustering.

Data Science - Clustering Work

Using Python for Data Science

An examination of Female Victimology using KMeans and DBSCAN techniques to discover patterns. Created as a capstone Project for Northwest Missouri State University.

Data Mining, Clustering and Classification

Desenvolvimento dos principais modelos de aprendizado de máquina supervisionado e não-supervisionado.

This repository contains all the retrieved Tweets and code used to elaborate each phase of the research methodology used in the paper 'Analyzing Food Trends on Twitter'.

Cluster Visualization Tool

📊🎯✨ Harness the power of the RFM (Recency, Frequency, Monetary) method to cluster customers based on their purchase behavior! Gain valuable insights into distinct customer segments, enabling you to optimize marketing strategies and drive business growth. 📈💡🚀

Clustering

Density-Based Spatial Clustering in Rain and Temperature

To Identify Major Customer Segments On Transnational Dataset Using Unsupervised ML Clustering Algorithms