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

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.

aparajitad60/The-Sparks-Foundation---Machine-Learning-Data-Science

This Repo Consists of some of the Tasks for The Sparks Foundation-Machine Learning and Data Science Internship, containing Supervised and Unsupervised Machine Learning Techniques to solve A ML Problem in a Systematic Way.

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.

shanuhalli/Assignment-PCA

Perform Principal component analysis and perform clustering using first 3 principal component scores both Heirarchial and K Means Clustering and obtain optimum number of clusters and check whether we have obtained same number of clusters with the original data.

vaitybharati/Hierarchical-Clustering

Hierarchical-Clustering

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.

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

AjmalSarwary/Preprocessing-for-Machine-Learning

Data prepration and preprocessing for predictive modeling with SAS and Python

Arif-Rehman/ExcelR_Assignment---Clustering---Assignment---7

ExcelR_Assignment---Clustering---Assignment---7

HoHasby/Hierarchial-clustering

Using Hierarchial clustering to categories the spending of customers into groups based on their spending habit and other features

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.

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.

raunaksatone5/Retail-Customer-Segmentation

Implemented K - means and Hierarchical clustering to cluster the retail customers into different segments, based on their spending habits. Employed RFM metrics and assigned labels to each customer based on RFM score.

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

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.

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.

Animesh227/Netflix-Movies-and-TV-Shows-Clustering

NETFLIX MOVIES AND TV SHOWS CLUSTERING is a project that aims to cluster the available movies and TV shows on Netflix based on their attributes such as genre, release year, and country of production.

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

PatilSukanya/Assignment-08-PCA

Used libraries and functions as follows:

saikrishnabudi/PCA-Principal-Component-Analysis

Data Science - PCA (Principal Component Analysis)

SINGHxTUSHAR/Assignment-75