GitHub topics: unsupervised-machine-learning
daniau23/customer_segment
Segmentation of customers using Agglomerative clustering and analysis using PowerBI
Language: Jupyter Notebook - Size: 3.76 MB - Last synced at: about 12 hours ago - Pushed at: about 13 hours ago - Stars: 1 - Forks: 0

udaycodespace/Unsupervised-Anime-Recommendation-System
A content-based anime recommendation system ⚡using unsupervised learning (K-Means). Suggests similar anime using synopsis & genre—no user history needed. Built during Edunet AI + Azure Internship.
Language: Jupyter Notebook - Size: 6.71 MB - Last synced at: 2 days ago - Pushed at: 2 days ago - Stars: 1 - Forks: 0

Liang-Team/Sequenzo
A fast, scalable, and intuitive Python package in social sequence analysis.
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SmartTensors/NMFk.jl
Nonnegative Matrix Factorization + k-means clustering and physics constraints for Unsupervised and Physics-Informed Machine Learning
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CrispenGari/ml-2023
💹📉📊📈This repository contains some machine leaning task that I did from the year 2023.
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GGasset/CudaNeatNetwork
Easy to use, Neural Network framework made from scratch in CUDA/C++, featuring LSTMs, able to train using Supervised learning and Evolution methods
Language: Cuda - Size: 736 KB - Last synced at: 4 days ago - Pushed at: 4 days ago - Stars: 1 - Forks: 0

amirabaskanov/valorant-team-optimizer
Clustering Player Archetypes to Optimize Team Composition in Valorant Esports
Language: Python - Size: 1.65 MB - Last synced at: 4 days ago - Pushed at: 4 days ago - Stars: 1 - Forks: 0

andreasMazur/variational_autoencoder
A light TensorFlow meta-class for variational autoencoder.
Language: Python - Size: 26.4 KB - Last synced at: 5 days ago - Pushed at: 5 days ago - Stars: 0 - Forks: 0

jiaxiaogang/HE
螺旋熵减系统
Language: Objective-C - Size: 225 MB - Last synced at: 5 days ago - Pushed at: 5 days ago - Stars: 326 - Forks: 49

jiaxiaogang/HELIX_THEORY
螺旋熵减理论
Language: Objective-C - Size: 90.2 MB - Last synced at: 5 days ago - Pushed at: 6 days ago - Stars: 137 - Forks: 35

nipunchauhan/Topic-Modeling-NLP-Python-Knime
This project compares topic modeling and text clustering techniques on BBC news articles. We use both KNIME and Python-based approaches to assess model quality and coherence in unsupervised text analysis.
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Sravyatogarla/Edureka-Data-Science-DIY
A complete collection of hands-on DIY projects from the Edureka Data Science 🔍📊Master Program, covering Python, Statistics, Machine Learning (Supervised & Unsupervised), NLP, Deep Learning (including Reinforcement Learning), Model Evaluation, and Tableau – organized by day and topic for structured learning.100 Days of Edureka Data Science DIY's
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Agoons20/Text_Mining_in_R
The projects here demonstrate how a textual corpus is prepared for analysis, preprocessing steps for computational text mining and extraction of business insights. Concepts such as feature representation using bag of words and TF-IDF are demonstrated, clustering and supervised machine learning algorithms like regression and others are used on a DTM
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sozelfist/handson-ml3 Fork of ageron/handson-ml3
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
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philiptitus/Mall-Customers
K-means Model to categorize Mall customers into different clusters based on their spending habits
Language: Jupyter Notebook - Size: 142 KB - Last synced at: about 9 hours ago - Pushed at: 11 days ago - Stars: 0 - Forks: 0

shaysingh818/dendritic
Iterative optimization library
Language: Rust - Size: 28.3 MB - Last synced at: 3 days ago - Pushed at: 3 days ago - Stars: 3 - Forks: 0

danial-hosseinpour/Machine-Learning-Projects
This repository showcases a collection of machine learning projects that I have worked on, applying various algorithms and techniques to solve real-world problems.
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SKT1803/iris-unsupervised-clustering
Unsupervised Machine Learning – Clustering on the Iris Dataset
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yaricom/goESHyperNEAT
The implementation of evolvable-substrate HyperNEAT algorithm in GO language. ES-HyperNEAT is an extension of the original HyperNEAT method for evolving large-scale artificial neural networks.
Language: Go - Size: 1.39 MB - Last synced at: 7 days ago - Pushed at: 14 days ago - Stars: 17 - Forks: 2

loudrxiv/frustrating
A new approach for cross-species prediction of transcription factor binding sites!
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jshah0000/Professional-Work
Data Analysis Projects
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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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ua-datalab/MLWorkshops
UArizona DataLab Workshops
Language: Jupyter Notebook - Size: 85.3 MB - Last synced at: 18 days ago - Pushed at: 18 days ago - Stars: 7 - Forks: 0

doxakis/HdbscanSharp
HDBSCAN in C#
Language: C# - Size: 2.52 MB - Last synced at: 4 days ago - Pushed at: about 1 month ago - Stars: 39 - Forks: 4

crimslack/economic_profile_clustering
A density- based analysis of global development levels through economic data clustering
Language: Python - Size: 23.4 KB - Last synced at: 20 days ago - Pushed at: 20 days ago - Stars: 0 - Forks: 0

greyhatguy007/Machine-Learning-Specialization-Coursera
Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
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kevinqnb/interpretable-clustering
Methods and algorithms for interpretable clustering. Example applications to climate data.
Language: Python - Size: 208 MB - Last synced at: 5 days ago - Pushed at: 21 days ago - Stars: 0 - Forks: 0

adobe/stringlifier
Stringlifier is on Opensource ML Library for detecting random strings in raw text. It can be used in sanitising logs, detecting accidentally exposed credentials and as a pre-processing step in unsupervised ML-based analysis of application text data.
Language: Python - Size: 7.35 MB - Last synced at: 14 days ago - Pushed at: 21 days ago - Stars: 167 - Forks: 28

Sravyatogarla/Unsupervised_ML_Project_Zoo_Dataset
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John-sam1983/John_Ndaa_Samson_Data_Science_Portfolio
This repository is a compilation of all the data science and in particular Machine Learning projects I have successfully carried out.
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Dharmeshgadhiya161/Netflix-Movies-and-TV-Shows-Clustering-Unsupervised-ML
Netflix Movies and TV Shows Clustering Unsupervised ML
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SmartTensors/GeoThermalCloud.jl
Geothermal Cloud for Machine Learning
Language: Jupyter Notebook - Size: 732 MB - Last synced at: 2 days ago - Pushed at: over 1 year ago - Stars: 29 - Forks: 4

Rahul-404/customer-segmentation
This project applies machine learning techniques to segment customers from a marketing campaign dataset. It uses demographic and behavioral data to uncover distinct customer groups, enabling more personalized marketing strategies and improved campaign targeting.
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zahra-ahmadbeigloo/Machine-Learning-Projects
This repository contains machine learning projects, where models are trained for classification, regression, clustering, and deep learning tasks. Each project includes data preprocessing, feature engineering, model training, evaluation, and visualizations to support findings.
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SalomonisLab/altanalyze3
AltAnalyze version 3 is a Python3 library to integrate and compare diverse RNA isoform datasets.
Language: Python - Size: 14 MB - Last synced at: 11 days ago - Pushed at: about 1 month ago - Stars: 6 - Forks: 3

dona-eric/Machine-Learning-with-Python-IBM-Laboratory
C'est une ressource importante pour tout les passionnées de la data science et du machine learning. J'ai collecté les ressources disponibles, les données et les notebooks de démarrage des cours proposés par IBM sur Coursera. Cette ressource vous permettra d'avoir un coup d'avance , de vous pratiquer et de passer votre certification
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dimitris-markopoulos/latent-semantic-clustering
Clustering book chapters with unsupervised ML—custom EM-GMM, sklearn baselines, and dimensionality reduction.
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AR-Version2/Intelligent-SAP-Financial-Integrity-Monitor
Intelligent SAP Financial Integrity Monitor (POC): Hybrid AI/ML (IF, LOF, AE) & rules-based anomaly detection on SAP FAGLFLEXA data using Python/Streamlit
Language: Python - Size: 4.05 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

theainerd/MLInterview
:octocat: A curated awesome list of AI Startups in India & Machine Learning Interview Guide. Feel free to contribute!
Size: 6.96 MB - Last synced at: about 1 month ago - Pushed at: about 4 years ago - Stars: 525 - Forks: 169

slalit360/Data-Science-ML-Cheat-Sheet-Books-Oreilly-
Data Science + ML Cheat Sheet collection by me
Language: Jupyter Notebook - Size: 208 MB - Last synced at: 28 days ago - Pushed at: about 2 years ago - Stars: 78 - Forks: 48

subhashsomarouthu/Netflix-Movies-and-TV-Shows-Clustering
Clustering similar content by matching text-based features and building a recommendation system
Language: Jupyter Notebook - Size: 19.7 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 1 - Forks: 0

acejolanda/mood-playlist-clustering
Using K-Means clustering to automatically generate mood-based playlists from Spotify audio features (project done at WBS coding school)
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albanecoiffe/telecom-recommender-system
This project implements a recommender system for telecom products and services, designed to suggest the most relevant offers to customers based on their behavior, usage patterns, and churn history.
Language: Jupyter Notebook - Size: 119 KB - Last synced at: about 10 hours ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

PhenomSG/ml-notebook
This project is designed for personal learning and exploration of fundamental machine learning concepts.
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Leox2f/credit_card_customer_segmentation
Customer segmentation analysis on credit card users to identify distinct customer groups based on their behavior and characteristics. The analysis uses unsupervised machine learning techniques, specifically K-means clustering, to group customers into meaningful segments.
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be-nny/music-genre-analysis-tool
This research proposes the use of unsupervised machine learning methods to partially get rid of the reliance for predetermined labels and instead let the clustering define the genres and like songs.
Language: Python - Size: 15.4 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0

kvitK1/ML-Driven-Clustering-of-Onboarding-Users-Strategies-for-Enhanced-Conversion
Bachelor thesis is submitted in fulfilment of the requirements for the Bachelor of Science degree in the Department of Business Analytics and Information Technologies at the Faculty of Applied Sciences of Ukrainian Catholic University.
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seanwood/gcc-nmf
Real-time GCC-NMF Blind Speech Separation and Enhancement
Language: Python - Size: 43.2 MB - Last synced at: 22 days ago - Pushed at: about 6 years ago - Stars: 319 - Forks: 134

iakovoskritikos/Machine-Learning
Machine Learning for Biomedical Engineers
Language: Jupyter Notebook - Size: 1.56 MB - Last synced at: 8 days ago - Pushed at: about 2 years ago - Stars: 4 - Forks: 2

nla-group/classix
Fast and explainable clustering in Python
Language: Python - Size: 297 MB - Last synced at: about 1 month ago - Pushed at: 4 months ago - Stars: 116 - Forks: 12

tejaswirupa/Unsupervised-Learning-Analysis-of-causes-of-death-among-children
Analyzed global child mortality data using PCA and clustering to identify cause-based patterns across 180+ countries. Revealed dominant mortality factors like respiratory infections and preterm birth in high-risk regions.
Language: Jupyter Notebook - Size: 7.02 MB - Last synced at: 9 days ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

OmarrAymann/Machine-learning-projects
A collection of machine learning projects covering supervised learning and unsupervised learning. Each project includes: Clean and reproducible code End-to-end pipeline: data preprocessing, modeling, evaluation, visualization Well-documented notebooks and scripts Use of popular ML libraries like Scikit-learn
Language: Jupyter Notebook - Size: 5.68 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

alvinadar/Hierarchical-Clustering
Agglomerative HC step by step concept
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measterpojo/Denoising-Autoencoders-DAEs-for-Domain-Adaptation
Denoising Autoencoders (DAEs) for Domain Adaptation using DAEs to find the invariant features for classification
Language: Jupyter Notebook - Size: 43 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

temulenbd/tb-unsupervised-learning
This is for my personal reference, where I compile codes and exercises that could be useful later on.
Language: Jupyter Notebook - Size: 291 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0

AVoss84/bayes-anomaly
A Python library for explainable Bayesian Anomaly Detection
Language: Jupyter Notebook - Size: 4.17 MB - Last synced at: 4 days ago - Pushed at: 2 months ago - Stars: 9 - Forks: 1

luofuli/DualRL
A Dual Reinforcement Learning Framework for Unsupervised Text Style Transfer (IJCAI 2019)
Language: Python - Size: 34.8 MB - Last synced at: about 2 months ago - Pushed at: about 5 years ago - Stars: 277 - Forks: 46

fatimagulomova/iu-projects
IU Projects
Language: Jupyter Notebook - Size: 127 MB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 0 - Forks: 0

havelhakimi/gene-expression
Agglomerative based clustering on gene expression dataset
Language: Jupyter Notebook - Size: 1.26 MB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 8 - Forks: 0

DragonflyRobotics/MAGIST-Algorithm
Multi-Agent Generally Intelligent Simultaneous Training Algorithm for Project Zeta
Language: Python - Size: 139 MB - Last synced at: 5 days ago - Pushed at: 3 months ago - Stars: 5 - Forks: 0

opencog/opencog
A framework for integrated Artificial Intelligence & Artificial General Intelligence (AGI)
Language: Scheme - Size: 178 MB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 2,370 - Forks: 727

aomdahl/gleanr_workflow
Sparse factorization framework to integrate GWAS studies and identify shared latent genetic components
Language: R - Size: 54.7 MB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 1 - Forks: 0

Hanhlevna/Manhos
This package aims to provide a platform for assessment of hotel online reviews. Datasets were collected from TripAdvisor and Booking.
Language: Python - Size: 7.81 KB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 0 - Forks: 0

Statistics-and-Machine-Learning-with-R/Statistical-Methods-and-Machine-Learning-in-R
This is an initiative to help understand Statistical methods and Machine learning in a naive manner. You will find scripts, and theoretical contents required to clarify concepts, especially for bio-informatic students.
Language: R - Size: 24.3 MB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 14 - Forks: 12

KenethGarcia/ClassiPyGRB
This repository contains all the updates, code, and documentation related to ClassiPyGRB.
Language: Python - Size: 371 MB - Last synced at: 9 days ago - Pushed at: 12 months ago - Stars: 17 - Forks: 2

yaricom/goNEAT
The GOLang implementation of NeuroEvolution of Augmented Topologies (NEAT) method to evolve and train Artificial Neural Networks without error back propagation
Language: Go - Size: 3.54 MB - Last synced at: 8 days ago - Pushed at: 6 months ago - Stars: 77 - Forks: 18

eudesgccunha/ecommerce-rfm-clustering
Customer clustering from RFM results for an e-commerce.
Size: 7.06 MB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 0 - Forks: 0

sushant1827/Creating-Customer-Segments
Machine Learning Nano-degree Project : To identify customer segments hidden in product spending data collected for customers of a wholesale distributor
Language: Jupyter Notebook - Size: 551 KB - Last synced at: 2 months ago - Pushed at: over 5 years ago - Stars: 1 - Forks: 0

Onyedikachi-E/customer_segmentation_deployment
This customer segmentation model. Check it out it is awsome and can be integrated on platforms
Language: Jupyter Notebook - Size: 487 KB - Last synced at: 2 months ago - Pushed at: 2 months ago - Stars: 0 - Forks: 0

1adityakadam/Footwear-Classification-with-Machine-Learning
This Machine Learning project uses K-means clustering and Expectation-Maximization (EM) algorithms to classify footwear types from the Footwear Kaggle dataset. Key features include image preprocessing, dimensionality reduction, and result visualization. The project explores unsupervised learning for footwear classification.
Language: Jupyter Notebook - Size: 1.8 MB - Last synced at: 2 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

philiptitus/Book-Recommendation
Recommender system using collaborative filtering algorithm for recommnding books to read
Language: Jupyter Notebook - Size: 4.28 MB - Last synced at: 2 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

nakulpandit/ml_1
Machine Learning
Language: Jupyter Notebook - Size: 2.86 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

Yaa-de-champ/Machine-Learning
for various machine learning projects
Language: Jupyter Notebook - Size: 31.6 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

yaricom/goNEAT_NS
This project provides GOLang implementation of Neuro-Evolution of Augmenting Topologies (NEAT) with Novelty Search optimization aimed to solve deceptive tasks with strong local optima
Language: Go - Size: 4.54 MB - Last synced at: 2 months ago - Pushed at: 6 months ago - Stars: 40 - Forks: 7

Pevicsanch/unsupervised-learning-classification
Learn how to use Python to performance unsupervised learning classification
Language: HTML - Size: 12.4 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

noar689/carbon-footprint-reduction
ML | recommendation system | low carbon products
Language: Jupyter Notebook - Size: 116 KB - Last synced at: 2 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

Molingejr/machine_learning_models
Applying machine learning models to make predictions and find patterns within data
Language: Jupyter Notebook - Size: 2.33 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

arush18/Brain-Tumor-Detection
Brain Tumor Detection using a VGG16-based CNN to classify MRI scans.
Language: Jupyter Notebook - Size: 121 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

nullHawk/k-means
Implementation of K-means algorithm from scratch with adaptive distance metrics
Language: Python - Size: 57.6 KB - Last synced at: 18 days ago - Pushed at: 3 months ago - Stars: 1 - Forks: 0

kevinwood15/Python_ML_KMeans_Project
This project uses the KMeans ML algorithm to identify segments of the broader population that form the core customer base of a company.
Language: Jupyter Notebook - Size: 275 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

McGill-MMA-EnterpriseAnalytics/PAWsitive-Tails-Shaping-Brighter-Futures-for-Shelter-Pets
This project is a comprehensive data science initiative focused on improving the lives of animals in shelters. We aim to leverage advanced analytical methods to predict shelter animal outcomes and optimize resource allocation.
Language: Jupyter Notebook - Size: 57.4 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 2

ayushcodes13/Machine-Learning-Practice
This repository contains hands-on projects and implementations of various machine learning techniques.
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CyprianFusi/Credit-Card-Customer-Segmentation-using-k-means-Algorithm
You are a data scientist working for a credit card company. You're asked to help segment a dataset containing information about the company’s clients into different groups to enable the company to apply different business strategies for each type of customer.
Language: Jupyter Notebook - Size: 2.71 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0

zenklinov/PCA
PCA is a statistical technique for reducing the dimensionality of a dataset
Language: R - Size: 183 KB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

zenklinov/Clustering_K-Means_Metrics_PCA
Comparing Euclidean Distance, Manhattan Distance, Cosine Distance, with PCA in K-Means Clustering
Language: Jupyter Notebook - Size: 479 KB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 1 - Forks: 0

virajbhutada/ML-projects
A collection of machine learning mini-projects and analyses developed using Jupyter Notebook. Each project demonstrates practical applications of machine learning algorithms on a variety of datasets, covering techniques from exploratory data analysis (EDA) to model training and evaluation.
Language: Jupyter Notebook - Size: 15.2 MB - Last synced at: 3 months ago - Pushed at: 7 months ago - Stars: 1 - Forks: 0

Shailesh-Padhariya/Online-Retail-Clustering
This project applies the K-Means clustering algorithm to segment customers based on their purchasing behavior. The dataset used contains transaction data for an online retail store, and the project aims to group customers using three key metrics: Recency, Frequency, and Monetary Value (RFM).
Language: Jupyter Notebook - Size: 0 Bytes - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 1 - Forks: 0

Birmingham-and-Solihull-ICS/Unsupervised-Clustering-Practices
K-means and hierarchical clustering of GP practices based on QOF performance measures
Size: 24.4 KB - Last synced at: 3 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

nafisalawalidris/Advanced-Fraud-Detection-with-Anomaly-Detection
This repository demonstrates how to build a robust fraud detection system that combines supervised learning techniques with anomaly detection models. It provides end-to-end implementation, from data preprocessing and model training to deploying a real-time fraud detection API using FastAPI.
Language: Jupyter Notebook - Size: 2 MB - Last synced at: 3 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

Ansh2709/Customer-Segmentation-ML-Project
Project segregates the customers on the basis of their spending score and annual income using K-Means Clustering that is a part of unsupervised learning
Language: Jupyter Notebook - Size: 45.9 KB - Last synced at: about 10 hours ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

FabianGroeger96/deep-embedded-music
Creation of an embedding space using unsupervised triplet loss and Tile2Vec that can be used for a variety of downstream tasks
Language: Jupyter Notebook - Size: 26.4 MB - Last synced at: about 1 month ago - Pushed at: almost 4 years ago - Stars: 18 - Forks: 2

microsoft/Data-Discovery-Toolkit 📦
A data discovery and manipulation toolset for unstructured data
Language: Jupyter Notebook - Size: 89.2 MB - Last synced at: 5 days ago - Pushed at: over 1 year ago - Stars: 54 - Forks: 12

ziatdinovmax/pyroVED
Invariant representation learning from imaging and spectral data
Language: Python - Size: 112 MB - Last synced at: 26 days ago - Pushed at: over 1 year ago - Stars: 50 - Forks: 11

poacosta/esesa-notebooks-1er-trimestre
ESESA Notebooks - Primer Trimestre
Language: Jupyter Notebook - Size: 2.72 MB - Last synced at: 2 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

vidhyarth08/Machine-Learning
Machine learning algorithms
Language: Jupyter Notebook - Size: 2.56 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

harshjuly12/Customer-Segmentation-Using-K-Means-Clustering
Repository for customer segmentation using KMeans clustering, utilizing techniques for data analysis and cluster identification. Includes dataset from Kaggle and open-source tools.
Language: Jupyter Notebook - Size: 2.28 MB - Last synced at: 2 months ago - Pushed at: 11 months ago - Stars: 10 - Forks: 3

DRehan003/Cluster_Analysis_of_Smart_Contract_Risks
I performed cluster analysis on a dataset of smart contracts in Python to identify similar risk profiles.
Language: Python - Size: 1.31 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

anhvu2201/Churn_Users_Prediction_using_Supervised_and_Unsupervised_ML
Develop and train an supervised machine learning model to identify potential churn users. Additionally, segment these users into distinct groups using an unsupervised machine learning model to enable tailored marketing strategies.
Language: Jupyter Notebook - Size: 2.23 MB - Last synced at: 3 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

DieStok/Basic-Machine-Learning-for-Bioinformatics
ML course materials for bioinformatics students following the Basic Machine Learning for Bioinformatics course at Utrecht University. Course created and taught by Dieter Stoker.
Language: Jupyter Notebook - Size: 87.1 MB - Last synced at: 3 months ago - Pushed at: over 2 years ago - Stars: 6 - Forks: 1

rayyan-merchant/PAI-Project
For our PAI course project, we are building several disease prediction systems, including heart disease, diabetes, Parkinson's, and breast cancer classification. Using machine learning algorithms, we aim to analyze patient data and improve the accuracy of early diagnosis, providing valuable insights to healthcare professionals.
Language: Python - Size: 912 KB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0
