dendogram

sandipanpaul21/Clustering-in-Python

Clustering methods in Machine Learning includes both theory and python code of each algorithm. Algorithms include K Mean, K Mode, Hierarchical, DB Scan and Gaussian Mixture Model GMM. Interview questions on clustering are also added in the end.

kirralabs/text-clustering

learn about indonesian text classification and topics modeling

yousefkotp/Network-Anomaly-Detection

This project focuses on network anomaly detection due to the exponential growth of network traffic and the rise of various anomalies such as cyber attacks, network failures, and hardware malfunctions. This project implement clustering algorithms from scratch, including K-means, Spectral Clustering, Hierarchical Clustering, and DBSCAN

shanuhalli/Assignment-Clustering

Perform Clustering (Hierarchical, K Means Clustering and DBSCAN) for the airlines and crime data to obtain optimum number of clusters. Draw the inferences from the clusters obtained.

vaitybharati/Assignment-07-Clustering-Hierarchical-Airlines-

Assignment-07-Clustering-Hierarchical-Airlines. Perform clustering (hierarchical) for the airlines data to obtain optimum number of clusters. Draw the inferences from the clusters obtained. Data Description: The file EastWestAirlinescontains information on passengers who belong to an airline’s frequent flier program. For each passenger the data include information on their mileage history and on different ways they accrued or spent miles in the last year. The goal is to try to identify clusters of passengers that have similar characteristics for the purpose of targeting different segments for different types of mileage offers.

VikramBansall/Cryptocurrency-Portfolio-Optimization

Utilized hierarchical clustering to identify the most similar cryptocurrency clusters and determine which currencies had the most significant impact on each other. Constructed a portfolio based on these findings.

shreyansh-2003/Clustering-Analysis-KMeans-vs-Agglomerative-Clustering-for-Large-Datasets

This repo explores KMeans and Agglomerative Clustering effectiveness in simplifying large datasets for ML. Goals include dataset download, finding optimal clusters via Elbow and Silhouette methods, comparing clustering techniques, validating optimal clusters, tuning hyperparameters. Detailed explanations and analysis are provided.

Abhik35/Assignment-Clustering-Hierarchical-Airlines

Perform clustering (hierarchical) for the airlines data to obtain optimum number of clusters. Draw the inferences from the clusters obtained. Data Description: The file EastWestAirlinescontains information on passengers who belong to an airline’s frequent flier program. For each passenger the data include information on their mileage history and on different ways they accrued or spent miles in the last year. The goal is to try to identify clusters of passengers that have similar characteristics for the purpose of targeting different segments for different types of mileage offers ID --Unique ID Balance--Number of miles eligible for award travel Qual_mile--Number of miles counted as qualifying for Topflight status cc1_miles -- Number of miles earned with freq. flyer credit card in the past 12 months: cc2_miles -- Number of miles earned with Rewards credit card in the past 12 months: cc3_miles -- Number of miles earned with Small Business credit card in the past 12 months: 1 = under 5,000 2 = 5,000 - 10,000 3 = 10,001 - 25,000 4 = 25,001 - 50,000 5 = over 50,000 Bonus_miles--Number of miles earned from non-flight bonus transactions in the past 12 months Bonus_trans--Number of non-flight bonus transactions in the past 12 months Flight_miles_12mo--Number of flight miles in the past 12 months Flight_trans_12--Number of flight transactions in the past 12 months Days_since_enrolled--Number of days since enrolled in flier program Award--whether that person had award flight (free flight) or not

amaurypm/rmsdmat

Superimpose a set of protein structures and report a RSMD matrix, in CSV and Mega-compatible formats.

Archan311/K_Means_EDA_PCA

Consensus Recommendation

dhimansaha18/Chracter-Map-Generation-with-NLP

This project is a step towards building an Artificial General Intelligence. The main goal is to discover an individual's biasses getting his/her field of interests from Instagram ad interests.

doguilmak/Clus-Hierarchical-Credit-Card

Hierarchical clustering analysis on Credit Card customers dataset.

feromes/Digressao-da-Complexidade-Morfologica

Trabalho Final de Graduação em Arquitetura e Urbanismo Apresentado ao Centro Universitário Belas Artes de São Paulo sobre a complexidade morfológica

sailyshah/Clustering-of-countries

The objective of this project is to categorise the countries using some socio-economic and health factors that determine the overall development of the country and then accordingly suggest the NGO the country which is in dire need of help.

vaitybharati/Hierarchical-Clustering

Hierarchical-Clustering

AjmalSarwary/Preprocessing-for-Machine-Learning

Data prepration and preprocessing for predictive modeling with SAS and Python

hugohiraoka/Credit_Card_Customer_Segmentation

Classification Model of Potential Credit Card Customers

KelgerNuek/Cinema-Market-Customer-Segmentation

This clustering analysis aims to provide valuable insights into the viability of introducing an original language cinema in Milan, Italy.

maryamteimouri/DataAnalysis-and-KnowledgeDiscovery

This project aims to practice the steps of Crisp Data Mining ( CRISP-DM ). The repository includes 3 phases, data understanding, supervised learning, and unsupervised learning.

nanan010/Clustering

Agglomerative Clustering from scratch without using built-in library with different hyper-parameters using Python and evaluated the cluster quality using intrinsic and extrinsic scores

Neemias-tech/R-studies

This is a R repository of studies that I made on some data sets. There are linear models, predicition models (boosting - bagging - RandomFlorest), clustering and dendograms.

Nicole-lq/ML_proyects

Compilation of various projects based on machine learning algorithms.

OCHOLA-EDDYPHIL/Clustering

This project performs hierarchical clustering on a dataset containing network usage and performance metrics. It includes data preprocessing, encoding, normalization, and visualization of clustering results using dendrograms. The purpose is to analyze and group similar data points, offering insights into patterns and relationships within the dataset

RudraChatterjee/Unsupervised_Learning-Clustering

This project explores and analyzes financial data of a number of securities, applies Hierarchical and K-means clustering to group securities and create cluster profiles to develop personalized portfolios and investment strategies for clients

sabitendu/Capstone_Project_On_Netflix_Movies_And_TV-Shows_Clustering

Explore a comprehensive analysis of Netflix's extensive collection of movies and TV shows, clustering them into distinct categories. This GitHub repository contains all the details, code, and insights into how we've organized and grouped the vast content library into meaningful clusters.

saikrishnabudi/Clustering

Data Science - Clustering Work

yujansaya/kaggle_customer_segmentation

Mall Customer Segmentation Data

akash18tripathi/Clustering-Exploration-on-Fashion-MNIST

This repository contains a Jupyter Notebook that explores various clustering techniques applied to the Fashion MNIST dataset like K-Means, Hierarchical,etc.

balaa-07/ForestFiresPrediction

Forest Fires Prediction using Unsupervised Learning

BenieAimeeBoni/Projet-OC-n9

Produire une étude de marché avec Python

DRehan003/Cluster_Analysis_Webacy

I performed cluster analysis on a dataset of smart contracts in Python to identify similar risk profiles.

fazeelibtesam/Brain_Tumor

Classification of Brain Tumor

saifalibaig/Customer-Segmentation-Using-Clustering

This project focuses on segmenting customers based on their spending behavior, age, income, and preferences using clustering algorithms like K-Means and Hierarchical Clustering. The outcome is a system that helps businesses understand different groups of customers to better tailor their marketing strategies.

saikrishnabudi/PCA-Principal-Component-Analysis

Data Science - PCA (Principal Component Analysis)

SINGHxTUSHAR/Assignment-75