AUST_CSE 4.2 Pattern Recognition Lab Codes and Experiments

Combination of unsupervised clustering and supervised classification to detect shill bidding on eBay.

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.

This project aims to classify Netflix shows into distinct clusters using machine learning algorithms. The objective is to enhance user experience by providing personalized show recommendations based on users' preferences.

This repository contains my solutions and implementations for assignments assigned during the Data Mining course.

Mall Customer Segmentation Data

AgglomerativeClustering for Responden Data Answer

Comparison of various distance metrics used in clustering techniques for unsupervised learning

Unsupervised-ML---Hierarchical-Clustering-University Data. Import libraries, Import dataset, Create Normalized data frame (considering only the numerical part of data), Create dendrograms, Create Clusters, Plot Clusters.

Repo contains my personal Machine Learning projects with emphasis on explanability and Insights that are relevant for various stake holders in a business.

By aligning marketing efforts with customer preferences and desires, this approach promises to enhance market presence and drive substantial sales growth.

This repository implements customer segmentation techniques to analyze credit card user behavior and identify distinct customer groups. By leveraging Python libraries like pandas, Scipy and scikit-learn.

Welcome to my Classical Learning Projects repository, where I showcase my work in the fields of supervised and unsupervised learning. Here, you'll find code and datasets for various projects, such as classification and clustering tasks, implemented using popular algorithms like decision trees, neural networks, and k-means.

Clustering and recognition of faces in a photo album

Performed KMeans, Agglomerative, Divisive, DBSCAN clustering on FIFA dataset along with outlier detection and cluster analysis

I used Agglomerative Hierarchical Clustering and K-Means Clustering. The goal of this project is to find the best way to characterize the variety of consumers that a wholesale distributor deals with

Coronavirus tweets NLP - Text Classification mini-project work for Data Science course, FCSE, Skopje

COVID-19 Survival Rate Prediction and Analysis Using Medical History of Patients in the US

Hierarchical Clustering of Leukemia Gene Expression Dataset