Topic: silhouette-score Goto Github
Some thing interesting about silhouette-score
Some thing interesting about silhouette-score
silhouette-score,Clustering K-Means with Streamlit App Deployment
User: aisyahaini
Home Page: https://klastering-kmeans.streamlit.app/
silhouette-score,It's the HAC algorithm that Im using to sort newspaper articles by news. You can adapt it to pretty much any type of text.
User: alex-j-b
silhouette-score,Customer segmentation using clustering
User: alokthakur93
silhouette-score,Unsupervised Machine Learning project for Netflix Movies and TV Shows Clustering. The main goal of this project is to create a content-based recommender system that recommends top 10 shows to users based on their viewing history.
User: apaulgithub
silhouette-score,Given the e-commerce data, k-means clustering algorithm is used to cluster customers with similar interest. The data was collected from a well known e-commerce website over a period of time based on the customer’s search profile.
User: bushra-ansari
silhouette-score,Iris dataset
User: ccmkaaa
silhouette-score,I aim to automate playlist creation for Moosic, a startup known for manual curation, using Machine Learning, while addressing skepticism about the ability of audio features to capture playlist "mood."
User: cintia0528
silhouette-score,Clustering usuarios de cartão de crédito usando KMeans.
User: dbbatalha
silhouette-score,It's the continuation of my kleanee_ClusteringAnalysis project, in which I include the Silhouette Method for KMeans Clustering.
User: domingosdeeulariadumba
silhouette-score,Analyze past orders and create innovative features to build a customer's segmentation.
User: etiennelardeur
silhouette-score,Clustered customers into distinct groups based on similarity among demographical and geographical parameters. Applied PCA to dispose insignificant and multi correlated variances. Defined optimal number of clusters for K-Means algorithm. Used Euclidian distance as a measure between centroids.
User: evgenygrobov
silhouette-score,кластеризация клиентов на основе их покупательской способности
User: exelero565
silhouette-score,A customer profiling project based on RFM (Recency, Frequency, Monetary) analysis using a dataset from an online retail company in the United Kingdom. The aim is to identify customer habits and create personalized marketing strategies for targeted advertising.
User: g4lius
silhouette-score,Clustream, Streamkm++ and metrics utilities C/C++ bindings for python
User: giuliano-macedo
silhouette-score,detect unique colors from an image and express it in 3D
User: incheonq
silhouette-score,All-in-1 notebook which applies different clustering (K-means, hierarchical, fuzzy, optics) and classification (AdaBoost, RandomForest, XGBoost, Custom) techniques for the best model.
User: jermynyeo
silhouette-score,Metis project 5/7
User: krystkowiakk
silhouette-score,Cryptocurrency classification system using dimensionality reduction with PCA & t-SNE and cluster analysis with K-Means
User: laurenemilyto
silhouette-score,The purpose of this project is to create customer segmentations by using similarity between products purchased between the users by using Natural Language Processing techniques and Clustering
User: marayyy
silhouette-score,Clustering Clients for Insiders Loyalty Program.
User: matheusventurads
silhouette-score,Pytorch implementation of standard metrics for clustering
User: maxschelski
silhouette-score,An end-to-end project on clustering (unsupervised ML)
User: mrafifrbbn
silhouette-score,Mining Mastodon for silent users
User: nancyp321
silhouette-score,Unsupervised learning with different types clustering algorithms..
User: neel7317
silhouette-score,Detecting ideal clusters from imdb's movie dataset to segment using unsupervised learning
User: nmargos
silhouette-score,An interactive approach to understanding Machine Learning using scikit-learn
Organization: packtworkshops
silhouette-score,K-means is a least-squares optimization problem, so is PCA. k-means tries to find the least-squares partition of the data. PCA finds the least-squares cluster membership vector.
User: rajeshidumalla
silhouette-score,Based on a user's preferred movie or TV show, Unsupervised Machine Learning-Netflix Recommender suggests Netflix movies and TV shows. These suggestions are based on a K-Means Clustering model. These algorithms base their recommendations on details about movies and tv shows, such as their genres and description.
User: raviatkumar
silhouette-score,Using NLP and a smart chatbot, this project gauges customer sentiments online, offering customization and real-time feedback. Employing TF-BOW-LDA and ML models, it empowers e-commerce decisions, culminating in an NLP course at uOttawa in 2023.
User: rimtouny
silhouette-score,Best Clustering using silhouette_score
User: rmerzouki
silhouette-score,The project involves performing clustering analysis (K-Means, Hierarchical clustering, visualization post PCA) to segregate stocks based on similar characteristics or with minimum correlation. Having a diversified portfolio tends to yield higher returns and face lower risk by tempering potential losses when the market is down.
User: rochitasundar
silhouette-score,Capstone Project for the IBM Professional Certificate on Coursera
User: rohithaug
silhouette-score,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
User: rudrachatterjee
silhouette-score,The objective of this project is to analyze the customers of a bank, categorize them with K-Means and Hierarchical Clustering and evaluate their distinct characteristics
User: s-chan11
silhouette-score,The goal of this project is to use clustering techniques to segment employees based on their absenteeism patterns and provide insights that can help organizations to reduce absenteeism and improve employee productivity.
User: saadtariq01dataanalyst
silhouette-score,Data Science - PCA (Principal Component Analysis)
User: saikrishnabudi
silhouette-score,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.
User: sailyshah
silhouette-score,This repository contains introductory notebook for clustering techniques like k-means, hierarchical and DB SCAN
User: sanketmaneds
silhouette-score,This repository contains introductory notebooks for principal component analysis.
User: sanketmaneds
silhouette-score,This project aims to assist stakeholders in selecting an optimal location for a new restaurant in Chennai, Tamil Nadu, India.
User: sanky18
silhouette-score,1.Digital Marketing Advertisement Data Segmentation using clustering techniques. 2. Identify Optimum Principal Components that explains the most variance in the Primary Census data.
User: saumya-jain09
silhouette-score,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.
User: shanuhalli
silhouette-score,To perform customer segmentation using Python unsupervised learning model
User: shioulu
silhouette-score,OptimalCluster is the Python implementation of various algorithms to find the optimal number of clusters. The algorithms include elbow, elbow-k_factor, silhouette, gap statistics, gap statistics with standard error, and gap statistics without log. Various types of visualizations are also supported.
User: shreyas-bk
Home Page: https://www.linkedin.com/in/shreyas-kera-027727178/
silhouette-score,This case requires to develop a customer segmentation to understand customer's behaviour and separate them in different groups according to their preferences, and once the division is done, this information can be given to marketing team so they can plan the strategy accordingly.
User: sidharth178
silhouette-score,This project demonstrates a Clustering Model using Python. An international humanitarian NGO that is committed to fighting poverty and providing the people of backward countries with basic amenities and relief during the time of disasters and natural calamities. It has been able to raise around $ 10 million. The model is needed to help decide how to use this money strategically and effectively. The significant issues that come while making this decision are mostly related to choosing the countries that are in the direst need of aid. The model is used to categorize the countries using some socio-economic and health factors that determine the overall development of the country.
User: smartnamdevoloper
silhouette-score,Leverage unsupervised machine-learning techniques (K-means) to segment mall customers
User: taweilo
Home Page: https://github.com/Taweilo/Mall_Customer_Segmentation
silhouette-score,This repository contains code for creating ml model for clustering
User: vaishnavithakre
silhouette-score,The wholesale distributor is considering changing its delivery service from currently 5 days a week to 3 days a week. However, the distributor will only make this change in delivery service for customers that react positively. How can the wholesale distributor use the customer segments to determine which customers, if any, would reach positively to the change in delivery service?
User: venkatesh-eranti
silhouette-score,This repository contains clustering techniques applied to minute weather data. It contains K-Means, Heirarchical Agglomerative clustering. I have applied various feature scaling techniques and explored the best one for our dataset
User: y656
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