unsupervised-machine-learning | Topic

Topic: "unsupervised-machine-learning"

V-MalM/Stock-Clustering-and-Prediction Fork of dschoen24/Stock-Prediction

To build, train and test LSTM model to forecast next day 'Close' price and to create diverse stock portfolios using k-means clustering to detect patterns in stocks that move similarly with an underlying trend i.e., for a given period, how stocks trend together.To deploy our findings to an app along with an interactive dashboard to predict the next day ‘Close’ for any given stock.

Language: Jupyter Notebook - Size: 58.1 MB - Last synced at: 3 months ago - Pushed at: over 3 years ago - Stars: 6 - Forks: 1

opsabarsec/E-commerce-customers-automatic-clustering

E-commerce customers automatic grouping by unsupervised ML/AI. Data from the Kaggle Olist dataset

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nrohani/MolecularSubtypes

Classifying Breast Cancer Molecular Subtypes

Language: Python - Size: 17.7 MB - Last synced at: over 1 year ago - Pushed at: over 4 years ago - Stars: 6 - Forks: 5

AAndonio/Unsupervised-Feature-Selection-NDFS

Unsupervised Feature Selection NDFS is a project that shows how to select features with NDFS algorithm

Language: Python - Size: 66.4 KB - Last synced at: over 2 years ago - Pushed at: almost 6 years ago - Stars: 6 - Forks: 0

fazanham/ExpectationMaximization

A class for unsupervised classification using Expectation Maximization

Language: C++ - Size: 162 KB - Last synced at: over 1 year ago - Pushed at: over 6 years ago - Stars: 6 - Forks: 3

PetoLau/UnsupervisedEnsembles

Unsupervised ensemble learning methods for time series forecasting. Bootstrap aggregating (bagging) for double-seasonal time series forecasting and its ensembles.

Language: R - Size: 19.5 KB - Last synced at: over 1 year ago - Pushed at: over 6 years ago - Stars: 6 - Forks: 4

DragonflyRobotics/MAGIST-Algorithm

Multi-Agent Generally Intelligent Simultaneous Training Algorithm for Project Zeta

Language: Python - Size: 139 MB - Last synced at: 7 days ago - Pushed at: 3 months ago - Stars: 5 - Forks: 0

andgoldschmidt/pyprotoclust

Python Prototype Clustering: an implementation of minimax linkage for hierarchical clustering

Language: C++ - Size: 6.32 MB - Last synced at: about 13 hours ago - Pushed at: almost 3 years ago - Stars: 5 - Forks: 0

SayamAlt/Bank-Customer-Segmentation

Successfully established a clustering model which can categorize the customers of a renowned Indian bank into several distinct groups, based on their behavior patterns and demographic details.

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IDB-FOR-DATASCIENCE/Unsupervised-ML-Modelling-for-Segmentation

Python Implementation of multiple unsupervised segmentation models and evaluating them through multiple evaluation metrics

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kon172verma/IIT-Delhi-Masters-Thesis

Using the Mass Media data, along with Census and GIS data, we wish to analyze the socio-economic growth in various Indian Districts. Some techniques used: Doc-2-Vec, Hierarchical Clustering, TF-IDF

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FarnoushRJ/MLAlgorithms

Python Implementation of Various Machine Learning Algorithms :robot: 🧠

Language: Python - Size: 1.36 MB - Last synced at: over 2 years ago - Pushed at: almost 5 years ago - Stars: 5 - Forks: 0

uchiiii/bss Fork of nrswn40k1/bss

工学博覧会 : 音源分離チーム

Language: Python - Size: 31.6 MB - Last synced at: about 2 hours ago - Pushed at: about 5 years ago - Stars: 5 - Forks: 5

selforgmap/som-cpp

Self Organizing Map (SOM) is a type of Artificial Neural Network (ANN) that is trained using an unsupervised, competitive learning to produce a low dimensional, discretized representation (feature map) of higher dimensional data.

Language: C++ - Size: 254 KB - Last synced at: over 1 year ago - Pushed at: over 6 years ago - Stars: 5 - Forks: 7

selforgmap/som-rust

Language: Rust - Size: 3.35 MB - Last synced at: over 2 years ago - Pushed at: over 6 years ago - Stars: 5 - Forks: 0

RoryQo/Student-Online-Learning-Adaptability-Project

Explore factors influencing students' adaptability to online learning through machine learning techniques, including Random Forest, SVM, and Neural Networks. Identify key characteristics and develop predictive models to enhance online education experiences.

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LinaYorda/missing-females-ml

This project analyses data from missing females in the USA. I have performed Exploratory Data Analysis(EDA), KMeans, and Spatial clustering.

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aymanibrahim/mlpy

Hands-on in-person workshop for Machine Learning with Python

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AnneLivia/ArtificialIntelligence

Algorithms implemented while studying Artificial Intelligence

Language: Jupyter Notebook - Size: 394 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 4 - Forks: 0

iakovoskritikos/Machine-Learning

Machine Learning for Biomedical Engineers

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sylvainma/Explorify

Photography Spot Exploration Using Unsupervised Machine Learning

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SNTSVV/HUDD-Toolset

Implementation of the Heatmap-based Unsupervised Debugging of DNNs (HUDD) toolset

Language: Python - Size: 790 KB - Last synced at: about 1 year ago - Pushed at: over 2 years ago - Stars: 4 - Forks: 0

Hamza-A-Ansari/TSF_DataScience_Internship

In this repository, I've added the tasks that I've completed during the Internship as Data Science and Business Analytics at "The Sparks Foundation"(TSF).

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SinaTabakhi/MAgentOmics

[EMBC 2022] Multi-agent Feature Selection for Integrative Multi-omics Analysis

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mhajij/Generalized_K-means_on_Graphs_Using_PageRank

Generalized K-means on graph is an algorithm that utilizes centrality measures such as PageRank, harmonic centrality, etc to obtain k-means clustering algorithm to directed and undirected graphs.

Language: Python - Size: 401 KB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 4 - Forks: 0

aspav/DSIT

Projects developed in the scope of the MSc program Data Science & Information Technologies (DSIT)/Bioinformatics-Biomedical Data Science at NKUA

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VenkateshBH99/KMEANS-Clustering-C-OPENMP-CUDA-MPI

Kmeans clustering using c , openmp , cuda and mpi program

Language: C - Size: 3.12 MB - Last synced at: over 2 years ago - Pushed at: over 4 years ago - Stars: 4 - Forks: 3

mirianfsilva/machine-learning-studies

Machine Learning studies. Current approaches: Data processing, model training, evaluation performance and parameter adjustment for better performance.

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devVipin01/Exploring_Unsupervised_Learning

This notebook will walk through some of the basics of Agglomerative Clustering.

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nordavinden/Mutual-Information-ICA

Independent component analysis and related techniques based on mutual information

Language: C - Size: 333 KB - Last synced at: over 1 year ago - Pushed at: almost 6 years ago - Stars: 4 - Forks: 0

Mrpatekful/translate

Unsupervised translation project for university course.

Language: Python - Size: 45.6 MB - Last synced at: about 2 years ago - Pushed at: over 6 years ago - Stars: 4 - Forks: 0

haleyxu816/identify-customer-segments

class project of Udacity data scientist nanodegree

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Davisy/Unsupervised_Machine_Learning-Clustering-

Learn basics of clustering methods in Unsupervised Machine Learning

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RRafiee/Gaussian-mixture-modelling

Gaussian mixture modelling - Unsupervised learning

Language: R - Size: 8.19 MB - Last synced at: over 1 year ago - Pushed at: about 8 years ago - Stars: 4 - Forks: 2

shaysingh818/dendritic

Iterative optimization library

Language: Rust - Size: 28.3 MB - Last synced at: 5 days ago - Pushed at: 5 days ago - Stars: 3 - Forks: 0

alvaro-concha/animal-behavior-analysis

animal-behavior-analysis is a Python repository to analyze animal behavior in an unsupervised fashion. It uses UMAP dimensionality reduction and watershed segmentation to classify preprocessed animal behavior data obtained from video-tracking animal body parts with LEAP or DeepLabCut.

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sanikamal/gan-diffusion-atoz

Generative Adversarial Networks in Pytorch and Tensorflow

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burkh4rt/Multimodal-Trajectory-Modeling

Code supplement for "Unsupervised multimodal modeling of cognitive and brain health trajectories for early dementia prediction"

Language: Python - Size: 153 KB - Last synced at: 2 months ago - Pushed at: about 1 year ago - Stars: 3 - Forks: 1

Navjotkhatri/NETFLIX-MOVIES-AND-TV-SHOWS-CLUSTERING

Unsupervised ML Netflix Movies and TV Shows Clustering is a powerful tool that enables the platform to group its vast library of content into similar categories, providing users with personalized recommendations and improving the overall user experience. This approach is data-driven and relies on unsupervised machine learning algorithms.

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adarshsahu2803/CryptoML-Web-App

A web-based tool for Ethereum profile clustering, offering enhanced investment insights for informed decision-making.

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vahadruya/Capstone-Project-Unsupervised-ML-Topic-Modelling

The project explores a dataset of 2225 BBC News Articles and identifies the major themes and topics present in them. Topic Modeling algorithms such as Latent DIrichlet Allocation and Latent Semantic Analysis have been implemented. Effetiveness of the method of vectorization has also been explored

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Sarah-Hesham-2022/Customer-Personality-Analysis

Using K Means and R Language, K-Means algorithm applied the elbow method to get the optimal k, which is equal to 7.

Size: 104 KB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 3 - Forks: 0

lpapailiou/neuralnetwork

A java library providing a configurable neural network. Supports supervised learning and genetic algorithm.

Language: Java - Size: 107 MB - Last synced at: 2 months ago - Pushed at: over 2 years ago - Stars: 3 - Forks: 1

evelynkyl/yue_nmt

Python scripts and datasets of the "Extremely Low-Resource Neural Machine Translation: A Case Study of Cantonese" project

Language: Python - Size: 143 MB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 3 - Forks: 1

zcebeci/fcvalid

Internal Validity Indexes for Fuzzy and Possibilistic Clustering

Language: R - Size: 157 KB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 3 - Forks: 1

Ashleshk/Machine-Learning-Data-Science-Deep-Learning

This Repository Consists All Courses, Projects and Online Learning Done in Context of Machine learning, Data Sceince And Deep Learning From Various Sources like Youtube, Coursera, Udemy And WEbsites like Scikit, Keras

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Peteresis/Cryptocurrency

Unsupervised Machine Learning analysis to find patterns in Cryptocurrencies market valuations.

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nickcafferry/tensorflow-doc-Chinese

⚗ Tensorflow机器学习指南, 欢迎访问新创建的网页https://tensorflow-doc-chinese.readthedocs.io/zh_CN/latest/?badge=latest。本项目是根据TensorFlow Machine Learning Cookbook翻译过来的，欢迎批评指正。

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srikhetramohanty/Data-Science-Portfolio

This is a repository created in line with my understanding & implementation of the major complex ideas in Machine Learning & Inferential Statistics while working as a data science professional in the industry.

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tandrimasingha/ML_Projects

Collection of my Supervised and Unsupervised Machine Learning Projects.

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north0n-FI/K-means-clustering-on-US-crime-data

Unsupervised machine learning using U.S. crime data and k-means clustering. Crime categories: murder, assault & rape in all 50 states in 1973.

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sm823zw/Music-Speech-Classification

Unsupervised Music Speech Classification using Gaussian Mixture Models (EM algorithm)

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gabriel-q-wang/Unsupervised-Image-Classification

An exploration and comparison of traditional image classifications tasks compared with novel "unsupervised" image classification models.

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Karan-Malik/RestrictedBoltzmannMachine

Python3 implementation of the Unsupervised Deep Learning Algorithm, Restricted Boltzmann Machine.

Language: Python - Size: 19.4 MB - Last synced at: 3 months ago - Pushed at: about 5 years ago - Stars: 3 - Forks: 1

LaxmiChaudhary/Classifying-silhouettes-of-vehicles

Unsupervised Learning (PCA) on Vehicle dataset

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JuzerShakir/Creating-Customer-Segments 📦

Applied Unsupervised Learning techniques on product spending data collected for customers of a wholesale distributor to identify customer segments hidden in the data.

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N-Elmer/CHAT-SUMMARIZER

CHAT 🗣️ SUMMARY 📈 ANALYSIS

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juan-gamero-salinas/climateready-survey-pamplona

This repository gives you access to the CLIMATEREADY survey dataset containing thermal comfort votes during the 2021 and 2022 heatwave periods in Pamplona, Spain, as well as other relevant parameters self-reported by surveyees (e.g. occupant characteristics and behaviour, key building/dwelling characteristics, sleep problems, heat-related symptoms)

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RoryQo/Happiest-Countries

Categorize the countries using Partitioning and K-mean clustering with the 2018 happiness survey that determines the overall happiness of the country. Then we can see the true happiest countries.

Language: R - Size: 315 KB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 2 - Forks: 0

RoryQo/Predictive-Analysis-of-Drug-Usage

Predict hard drug use with supervised learning models including random forests, and naive bayes model; using accuracy and precision rates to assess the usefulness and validity of the models.

Language: R - Size: 216 KB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 2 - Forks: 0

jonathanbatty/stata-nmf

Non-negative Matrix Factorisation for Stata.

Language: Stata - Size: 22.3 MB - Last synced at: 2 months ago - Pushed at: 9 months ago - Stars: 2 - Forks: 0

txtasad/Ascii-Image-Art

Python library for converting images into ASCII character strings and ASCII character colored images.

Language: Python - Size: 2.45 MB - Last synced at: 12 days ago - Pushed at: 12 months ago - Stars: 2 - Forks: 0

surjyaneeh/Machine_Learning_Tutorial

This overview to machine learning offers a summary of its background, fundamental definitions, applications, and currently available challenges.

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MohamedRebai41/Ripple_Backend

Ripple is an AI-driven influencer marketing platform. This microservice enables interactive semantic search, classification, similarity search, and more, providing advanced tools for effective influencer discovery and engagement.

Language: Python - Size: 30.3 KB - Last synced at: 12 months ago - Pushed at: about 1 year ago - Stars: 2 - Forks: 0

ChryssaNab/Machine_Learning-AUEB

This repository hosts the programming exercises for the course "Machine Learning" of AUEB Informatics.

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Autosuffisant/Epitech-Unsupervised-Learning-And-Agents

Project part of the M-MLR-901 unsupervised learning module of @EPITECH, made with @OMaxime68

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palubad/S1BAM-IGARSS-2023

This code repository is an attachment for the IGARSS 2023 proceeding paper: Paluba D. et al. (2023): "Unsupervised Burned Area Mapping in Greece: Investigating the impact of precipitation, pre- and post-processing of Sentinel-1 data in Google Earth Engine".

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arienugroho050396/Customer-Personality-Analysis

Performing an unsupervised clustering of data on the customer's records from a groceries firm's database with K-Means.

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tstran155/Cluster-analysis-of-pressure-decline-during-solute-transport-in-bulk-liquid

In this notebook, I used unsupervised machine learning algorithms (K-Means and K-Plane) to cluster times series data.

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SaicharanKarri/Academic-Projects

This repository contains a collection of academic projects completed by me during my studies. These projects cover a wide range of topics including computer science, data analysis, and engineering. Each project includes detailed documentation and code.

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abhinav4201/UnSupervised-ML-Zomato-Restaurant-Clustering-and-Sentiment-Analysis

The Project focuses on Customers and Company, you have to analyze the sentiments of the reviews given by the customer in the data and made some useful conclusion in the form of Visualizations. Also, cluster the zomato restaurants into different segments. The data is visualized as it becomes easy to analyse data at instant.

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sashakttripathi/ExMax-MixtureOfGaussians

Find Clusters of data using Expectation Maximization algorithm on mixture of gaussians

Language: Python - Size: 199 KB - Last synced at: almost 2 years ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 0

mosaico-anr/cg-ano-detect-eval

Code of the evaluation paper "Assessing Unsupervised ML solutions for Anomaly Detection in Cloud Gaming Sessions" (CNSM/HiPNet 2022)

Language: Python - Size: 29.3 KB - Last synced at: almost 2 years ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 0

munozariasjm/plt-anomaly-detector

Automatiic Anomaly detetcion tool for CMS-PLT

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VetlaPavanKalyan/Unsupervised-Learning

This project is done by me.

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shogunbanik18/Custoseg

Custoseg is an algorithmic Marketing based Project to do Customer Segmentation using KMean Clustering Algorithm and targeted Recommendations based on each segment

Language: Jupyter Notebook - Size: 118 KB - Last synced at: 3 months ago - Pushed at: almost 3 years ago - Stars: 2 - Forks: 1

nikunjsonule/Book-Recommendation-System

A recommendation engine is a class of machine learning which offers relevant suggestions to the customer. A recommendation system is one of the top applications of data science. Every consumer Internet company requires a recommendation system like Netflix, YouTube, a news feed, etc. What you want to show out of a huge range of items is a recommendation system. Before the recommendation system, the major tendency to buy was to take a suggestion from friends. But Now Google knows what news you will read, YouTube knows what type of videos you will watch based on your search history, watch history, or purchase history. We were provided with ‘Book Recommendation System’ dataset to perform machine learning task, were to get insights from users-items interactions and provide best recommendation to users.

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pinkychow1010/VIIRS_Fire_ML_Clustering

Detecting active fire hotspots and unsupervised clustering hotspots using VIIRS thermal remote sensing data.

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Vishal-Padia/Anime_Recommender

As the name says

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BhakeSart/Customer-Segmentation

Customer segmentation is the process of dividing customers into groups based on common characteristics so companies can market to each group effectively and appropriately. This Project uses R language and Kmeans clustering algorithm to segment customers into clusters.

Language: R - Size: 22.6 MB - Last synced at: over 1 year ago - Pushed at: about 3 years ago - Stars: 2 - Forks: 1

deeplearningunb/pop-music

Language: Python - Size: 17.6 KB - Last synced at: over 1 year ago - Pushed at: about 3 years ago - Stars: 2 - Forks: 0

CwLiuzzZ/bolt-variance-distribution-model

Official code for bolt anomaly detection based on variance distribution model in haphazard environment.

Language: Python - Size: 69.3 MB - Last synced at: about 1 year ago - Pushed at: about 3 years ago - Stars: 2 - Forks: 0

exajobs/artificial-intelligence-collection

A collection of awesome software, libraries, Learning Tutorials, documents, books, resources and interesting stuff about Artificial Intelligence

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josephchancey/crypto-clustering

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SColson82/Cryptocurrency

Cluster and explore cryptocurrency using unsupervised machine learning for the purposes of creating a classification system for a new cryptocurrency investment portfolio option on the behalf of a client.

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SharathHebbar/Customer-segmentation

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IshtyM/KMeans-on-Iris-Data

Unsupervised algorithm on the common data i.e. iris

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Marcus-V-Freitas/Analise_Correspondencia_Covid

Demonstrativo da análise não supervisionada de Correspondência Simples com por países e grau de letalidade da Covid-19.

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MohamedSebaie/Algorithm-WorkShop-In_Python-ITI_Clustering_Project

Clustering Algorithms (KMeans, MeanShift, (Merged KMean and MeanShift) and DBSCAN)

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ElsevierSoftwareX/SOFTX-D-21-00016 Fork of djkurran/MWSegEval

MWSegEval is an image analysis toolbox that employs methods to automatically segment medical microwave breast images into regions of interest corresponding to various tissue types. To cite this software publication: https://www.sciencedirect.com/science/article/pii/S2352711021000674

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tienl/Cryptocurrencies

Crypto-currencies via unsupervised machine learning and data analysis.

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isaacarroyov/crime_analysis_mx2017

Comparing the Elbow Method and Silhouette Method for choosing the optimal number of clusters in K-Means algorithm

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Chhavi-Trivedi/Prediction-using-Unsupervised-ML

K-means clustering of iris dataset with visualization.

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satyamroy15/K-Means-Clustering-Unsupervised-ML

To predict the optimum number of clusters and represent it visually, from the given ‘Iris’ dataset.

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vicky60629/Segmentation-of-Credit-Card-Customers

Segmentation of Credit Card Customers

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atifc2/Sentiment-Analysis-of-Unsupervised-Data

Sentiment Analysis of Books and Its impact on children using Deep Learning

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shishir349/Clustering-Analysis-on-Mall-Customers

Problem Statement: This data set is created only for the learning purpose of the customer segmentation concepts , also known as market basket analysis . I will demonstrate this by using unsupervised ML technique (KMeans Clustering Algorithm) in the simplest form.You are owing a supermarket mall and through membership cards , you have some basic data about your customers like Customer ID, age, gender, annual income and spending score. Problem Statement You own the mall and want to understand the customers like who can be easily converge [Target Customers] so that the sense can be given to marketing team and plan the strategy accordingly.

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