AliAmini93/Fault-Detection-in-DC-microgrids

Using DIgSILENT, a smart-grid case study was designed for data collection, followed by feature extraction using FFT and DWT. Post-extraction, feature selection. CNN-based and extensive machine learning techniques were then applied for fault detection.

Language: Jupyter Notebook - Size: 20 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 58 - Forks: 3

saccofrancesco/deepshot

DeepShot is a machine learning model designed to predict NBA game outcomes using advanced team statistics and rolling averages. It combines historical performance trends with contextual game data to deliver highly accurate win predictions (71%)

Language: Jupyter Notebook - Size: 74.9 MB - Last synced at: 5 days ago - Pushed at: 5 days ago - Stars: 41 - Forks: 6

amzn/confident-sinkhorn-allocation

Pseudo-labeling for tabular data

Language: Jupyter Notebook - Size: 51.7 MB - Last synced at: about 1 month ago - Pushed at: 12 months ago - Stars: 23 - Forks: 7

Dalageo/ML-TitanicShipwreck

Exploring the World's Most Renowned Shipwreck 🚢

Language: Jupyter Notebook - Size: 990 KB - Last synced at: 2 months ago - Pushed at: 6 months ago - Stars: 12 - Forks: 2

edaaydinea/OP1-Prediction-of-the-Different-Progressive-Levels-of-Alzheimer-s-Disease

This is an optional model development project on a real dataset related to predicting the different progressive levels of Alzheimer’s disease (AD).

Language: Jupyter Notebook - Size: 47.5 MB - Last synced at: 2 months ago - Pushed at: over 2 years ago - Stars: 10 - Forks: 4

aj1365/DeepForest-Wetland-Paper

Here are the codes for the "Deep Forest classifier for wetland mapping using the combination of Sentinel-1 and Sentinel-2 data" paper.

Language: Jupyter Notebook - Size: 70.3 KB - Last synced at: about 2 years ago - Pushed at: about 3 years ago - Stars: 10 - Forks: 1

czaloumi/fire-risk-analysis

Machine Learning in Python to assess fire risk in satellite imagery and environmental conditions.

Language: Jupyter Notebook - Size: 57.9 MB - Last synced at: over 1 year ago - Pushed at: about 4 years ago - Stars: 10 - Forks: 6

edaaydinea/OP2-Prediction-of-the-Different-Progressive-Levels-of-Alzheimer-s-Disease-with-MRI-data

This is an optional model development project on a real dataset related to predicting the different progressive levels of Alzheimer’s disease (AD) with MRI data.

Language: Jupyter Notebook - Size: 16.9 MB - Last synced at: 2 months ago - Pushed at: over 2 years ago - Stars: 9 - Forks: 1

ashishrana1501/Forest-Fire-Prediction

Algerian Forest Fire Prediction

Language: Jupyter Notebook - Size: 4.01 MB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 9 - Forks: 2

xxl4tomxu98/autoencoder-feature-extraction

Use auto encoder feature extraction to facilitate classification model prediction accuracy using gradient boosting models

Language: Jupyter Notebook - Size: 90.1 MB - Last synced at: over 2 years ago - Pushed at: about 3 years ago - Stars: 9 - Forks: 1

tanishq-ctrl/House-price-prediction-and-visualization

This repository contains code and data for analyzing real estate trends, predicting house prices, estimating time on the market, and building an interactive dashboard for visualization. It is structured to cater to data scientists, real estate analysts, and developers looking to understand property market dynamics.

Language: Jupyter Notebook - Size: 20 MB - Last synced at: 3 months ago - Pushed at: 5 months ago - Stars: 8 - Forks: 0

rochitasundar/Customer-profiling-using-ML-EasyVisa

The aim is to find an optimal ML model (Decision Tree, Random Forest, Bagging or Boosting Classifiers with Hyper-parameter Tuning) to predict visa statuses for work visa applicants to US. This will help decrease the time spent processing applications (currently increasing at a rate of >9% annually) while formulating suitable profile of candidates more likely to have the visa certified.

Language: Jupyter Notebook - Size: 7.68 MB - Last synced at: over 2 years ago - Pushed at: over 3 years ago - Stars: 6 - Forks: 2

MainakVerse/Adamas-AI

Adamas AI is your smart companion for diamond valuation and knowledge. Using advanced machine learning, we provide accurate price predictions and expert advice.

Language: Jupyter Notebook - Size: 2.71 MB - Last synced at: 28 days ago - Pushed at: 28 days ago - Stars: 5 - Forks: 0

ChaitanyaC22/Fraud_Analytics_Credit_Card_Fraud_Detection

The aim of this project is to predict fraudulent credit card transactions with the help of different machine learning models.

Language: Jupyter Notebook - Size: 67.3 MB - Last synced at: about 2 months ago - Pushed at: over 2 years ago - Stars: 5 - Forks: 2

dipesg/Insurance_Fraud

Webapp that predict whether a claim is a fraudulent or not by asking user to put a csv file as mention in schema.json.

Language: Python - Size: 622 KB - Last synced at: over 2 years ago - Pushed at: about 3 years ago - Stars: 5 - Forks: 0

emykes/Flu_Vaccination_ML

The aim of this study is to predict how likely individuals are to receive their H1N1 flu vaccine. We believe the prediction outputs (model and analysis) of this study will give public health professionals and policy makers, as an end user, a clear understanding of factors associated with low vaccination rates. This in turn, enables end users to systematically act on those features hindering people to get vaccinated.

Language: Jupyter Notebook - Size: 4.92 MB - Last synced at: 8 months ago - Pushed at: over 3 years ago - Stars: 5 - Forks: 1

AbhishekGit-hash/Credit-Card-Lead-Prediction

A machine learning model to predict whether a customer will be interested to take up a credit card, based on the customer details and its relationship with the bank.

Language: Jupyter Notebook - Size: 11.3 MB - Last synced at: over 1 year ago - Pushed at: over 3 years ago - Stars: 5 - Forks: 0

merb92/Tanzanian-Waterpoint-Analysis-and-Classifictation

Predict the operational status of waterpoints to help the Tanzanian Government provide more clean water to its population using a Machine Learning Classifier

Language: Jupyter Notebook - Size: 34.5 MB - Last synced at: over 2 years ago - Pushed at: over 4 years ago - Stars: 5 - Forks: 2

MohamedMostafa010/ExeRay

ExeShield AI detects malicious Windows executables using ML. Analyzes entropy, imports, and metadata for rapid classification, aiding incident response. Built with Python and scikit-learn.

Language: Python - Size: 2.06 MB - Last synced at: 8 days ago - Pushed at: 9 days ago - Stars: 4 - Forks: 0

santiagocanepa/Insta_Bot

AI-powered Instagram bot for precise gender targeting using XGBoost and OpenAI ADA, with 91% accuracy at just $0.001 per 1000 queries. Automates follows/unfollows from user lists or photo likes, and checks follow-backs with randomized human-like actions. Ideal for influencers and marketers aiming for targeted engagement.

Language: TypeScript - Size: 22.3 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 4 - Forks: 0

gvarun20/Machine-learning_Simple_projects

use the data set and run the ipynb file

Language: Jupyter Notebook - Size: 50.1 MB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 4 - Forks: 0

pavankethavath/Microsoft-Classifying-Cybersecurity-Incidents-with-ML

A machine learning pipeline for classifying cybersecurity incidents as True Positive(TP), Benign Positive(BP), or False Positive(FP) using the Microsoft GUIDE dataset. Features advanced preprocessing, XGBoost optimization, SMOTE, SHAP analysis, and deployment-ready models. Tools: Python, scikit-learn, XGBoost, LightGBM, SHAP and imbalanced-learn

Language: Jupyter Notebook - Size: 4.54 MB - Last synced at: 3 days ago - Pushed at: 6 months ago - Stars: 4 - Forks: 0

Pratik94229/Credit-Card-Default-Prediction-End-to-End-Project

This is an end-to-end project that focuses on predicting credit card default using machine learning techniques. The project includes data validation,data preprocessing, model training, evaluation, and deployment.

Language: Jupyter Notebook - Size: 9.64 MB - Last synced at: about 1 year ago - Pushed at: almost 2 years ago - Stars: 4 - Forks: 0

cconsta1/SexEst_Notebooks

Example notebooks to produce the models used in the SexEst web application.

Language: Jupyter Notebook - Size: 581 KB - Last synced at: 2 months ago - Pushed at: over 2 years ago - Stars: 4 - Forks: 0

zahrasalarian/Data-Mining-Playground

This repository contains five mini projects covering several main topics in Data Mining, such as data preprocessing, clustering and classification.

Language: Jupyter Notebook - Size: 3.58 MB - Last synced at: over 1 year ago - Pushed at: almost 3 years ago - Stars: 4 - Forks: 0

michplunkett/ucpd-incident-scraper

This code is going to be used to scrape the UCPD Daily Incident page at a pre-determined frequency and store the incidents on a generic JSON data-store.

Language: Python - Size: 52.1 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 3 - Forks: 2

galvinguy2002/Loan-Prediction-

Loan Prediction using machine learning

Language: Jupyter Notebook - Size: 342 KB - Last synced at: about 1 year ago - Pushed at: over 1 year ago - Stars: 3 - Forks: 0

ShivamVadalia/Underwater-Waste-Detection-Using-YoloV8-And-Water-Quality-Assessment

Neural Ocean is a project that addresses the issue of growing underwater waste in oceans and seas. It offers three solutions: YoloV8 Algorithm-based underwater waste detection, a rule-based classifier for aquatic life habitat assessment, and a Machine Learning model for water classification as fit for drinking or irrigation or not fit.

Language: Jupyter Notebook - Size: 21.6 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 3 - Forks: 1

Darshbhi99/Sensor-Fault-Detection

This Project we take Data of the sensor in brake system used in Heavy Duty Vehicles and Detect whether the System Failure is because of APS or not using Machine Learning Model which can be continuously trained and used for Prediction. I have Created WebApp using FASTAPI and deployed on AWS EC2 as a Docker Image through ECR Repositories

Language: Jupyter Notebook - Size: 2.47 MB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 3 - Forks: 0

SunilGolden/Tomato-Leaf-Disease-Classifier

Language: Jupyter Notebook - Size: 6.46 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 3 - Forks: 0

apoorvaKR12695/Mobile-Price-Range-Prediction

Supervised ML- Built a Multi-Class classification model to find the relation between features of a mobile phone(RAM, Internal Memory etc) and its selling price. Model will predict the price range indicating how high the price is.

Language: Jupyter Notebook - Size: 6.83 MB - Last synced at: almost 2 years ago - Pushed at: almost 3 years ago - Stars: 3 - Forks: 4

akthammomani/Credit_Risk_Classification

Classification Modeling: Probability of Default

Language: Jupyter Notebook - Size: 10.3 MB - Last synced at: almost 2 years ago - Pushed at: over 3 years ago - Stars: 3 - Forks: 1

mandar196/Hate_Speech_Detection-NLP

Created Hate speech detection model using Count Vectorizer & XGBoost Classifier with an Accuracy upto 0.9471, which can be used to predict tweets which are hate or non-hate.

Language: Jupyter Notebook - Size: 27.3 KB - Last synced at: over 2 years ago - Pushed at: over 4 years ago - Stars: 3 - Forks: 3

DarkMattrMaestro/stats-tmnf-quarto

Un rapport statistique à but d'analyser la relation entre l’étiquette et le cheminement de circuits dans TMNF utilisant la classification

Language: TeX - Size: 31 MB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 2 - Forks: 0

pregismond/northstar-snowparkml-modeling

Predicting Food Truck Locations Using Snowpark ML and XGBoost

Language: Jupyter Notebook - Size: 2.94 MB - Last synced at: about 2 months ago - Pushed at: 4 months ago - Stars: 2 - Forks: 1

TomerYS/Medical-Data-Classifier

ML model for Kaggle competition: TAU Intro2DS - Final Assignment - Spring 2023

Language: Python - Size: 1.18 GB - Last synced at: about 2 months ago - Pushed at: 4 months ago - Stars: 2 - Forks: 0

SimranS22/Heart-Disease-Prediction-Model-SurTech

A ML application(deployed on flask) to detect heart disease in patients based on medical features.

Language: Jupyter Notebook - Size: 8.26 MB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 2 - Forks: 1

SeyedMuhammadHosseinMousavi/PSO-Fuzzy-XGBoost-Classifier-Boosted-with-Neural-Gas-Features-on-EEG-Signals-in-Emotion-Recognition

PSO Fuzzy XGBoost Classifier Boosted with Neural Gas Features on EEG Signals in Emotion Recognition

Language: Python - Size: 1.13 MB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 2 - Forks: 0

moayadeldin/DiaLoop

Android/iOS app for Diabetes monitoring and prediction. (UI-based features & Predictive Analysis using Deep Learning)

Language: Dart - Size: 2.94 MB - Last synced at: 6 months ago - Pushed at: 6 months ago - Stars: 2 - Forks: 0

slrvv/CENTRE

Language: R - Size: 434 MB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 2 - Forks: 3

RuiFSP/mlzoomcamp2024-midterm-project

Midterm project for mlzoomcamp 2024

Language: Jupyter Notebook - Size: 43.1 MB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 2 - Forks: 0

cego669/DatathonEngopeVI

Equipe: Embrapeiros. Solução proposta para o Datathon do VI ENGOPE (Encontro Goiano de Probabilidade e Estatística). Obs: FOMOS CAMPEÕES!!!!!!!!

Language: Jupyter Notebook - Size: 3.43 MB - Last synced at: 2 months ago - Pushed at: 8 months ago - Stars: 2 - Forks: 1

oladimeji-kazeem/bank-customer-churn-predictor

Customer churn is a critical issue for banks, as retaining customers is more cost-effective than acquiring new ones. This project aims to analyse customer churn in a bank and develop a predictive model to identify customers who are likely to leave, and the responsible factors.

Language: Python - Size: 5.25 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 2 - Forks: 1

Nishant2018/classification-with-nlp-xgboost-and-pipelines

Natural Language Processing (NLP) is a field of artificial intelligence that focuses on the interaction between computers and humans through natural language.

Language: Jupyter Notebook - Size: 24.4 KB - Last synced at: 3 months ago - Pushed at: 12 months ago - Stars: 2 - Forks: 0

Nishant2018/Academic-Success-Classification-XGBoost-

XGBoost is an open-source machine learning library that provides efficient and scalable implementations of gradient boosting algorithms. It is known for its speed, performance, and accuracy, making it one of the most popular and widely-used machine learning libraries in the data science community.

Language: Jupyter Notebook - Size: 7.03 MB - Last synced at: 9 days ago - Pushed at: about 1 year ago - Stars: 2 - Forks: 0

StrangeCoder1729/FinancialFraudDetectionModels

Developed and evaluated machine learning and deep learning models for detecting financial fraud.

Language: Jupyter Notebook - Size: 2.58 MB - Last synced at: 6 months ago - Pushed at: about 1 year ago - Stars: 2 - Forks: 1

karthik-d/FungiCLEF-2022-using-Network-Ensembles

Scripts, figures and working notes for the participation in FungiCLEF-2022, part of the 13th CLEF Conference, 2022

Language: Python - Size: 15.5 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 2 - Forks: 2

SINGHxTUSHAR/Credit-Card-Fraud-Detection

Credit-Card-Fraud-Detection project is a binary classification project which predicts the Fraud by using the different classification algorithms

Language: Jupyter Notebook - Size: 2.75 MB - Last synced at: 22 days ago - Pushed at: about 1 year ago - Stars: 2 - Forks: 0

grknc/Customer-Churn-Analyzer-with-ML

Telco Churn Analysis and Modeling is a comprehensive project focused on understanding and predicting customer churn in the telecommunications industry. Utilizing advanced data analysis and machine learning techniques, this project aims to provide insights into customer behavior and help develop effective strategies for customer

Language: Jupyter Notebook - Size: 3.09 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 2 - Forks: 0

nicolaivicol/ml-pred-default-deploy-aws-sagemaker

Modelling and prediction of default + deployment via AWS Sagemaker

Language: HTML - Size: 10.3 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 2 - Forks: 0

keerthikkn/Aviation_delay_prediction

flight delay prediction using XGboost classifier

Language: Jupyter Notebook - Size: 4.99 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 2 - Forks: 0

LuluW8071/Twitter-Fake-Profile-Detection

Machine learning models for identifying real-time fake profiles on Twitter

Language: Jupyter Notebook - Size: 603 KB - Last synced at: 3 months ago - Pushed at: over 1 year ago - Stars: 2 - Forks: 0

Siddharth1989/LearnerCentricFeedbackEnhancement

Developing a feedback theory-informed natural language processing (NLP) model to enable large-scale evaluation of written feedback, and analysing a large set of feedback extracted from Moodle using this model to understand the presence of student-centred feedback elements, the commonality and differences in feedback provision across disciplines.

Language: Jupyter Notebook - Size: 5.22 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 2 - Forks: 0

Billie-LS/Trading_ML_Algo_Experimentation

Variety of Jupyter Lab files examining different ML code for trading using yFinance

Language: Jupyter Notebook - Size: 1.01 MB - Last synced at: about 2 years ago - Pushed at: about 2 years ago - Stars: 2 - Forks: 0

santurini/Heart-Rate-Zones-Prediction

The aim of this work was to predict the heart rate zones. To do this we applied several data transformation techniques which we then used to pull an Xgboost model.

Language: Jupyter Notebook - Size: 55.7 KB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 0

parulsharma098/Cardiovascular-Risk-Prediction

This Project is based upon a CHDs (Cardiovascular Heart Diseases) research dataset which has over 3000 records and 16 attributes. Since, the target variable belongs to Categorical attribute, We built classification models for the future predictions of CHDs in patients considering the features.

Language: Jupyter Notebook - Size: 9.09 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 0

mohammadtavakoli78/Data-Mining

This is projects of Data Mining

Language: Jupyter Notebook - Size: 7.93 MB - Last synced at: over 2 years ago - Pushed at: almost 3 years ago - Stars: 2 - Forks: 1

hedzd/AUT-Datamining-projects

Projects and practical assignments for data mining course at AUT, spring 2022. Projects contain main topics in data mining, such as data preprocessing, clustering, classification and assosiation rules.

Language: Jupyter Notebook - Size: 3.22 MB - Last synced at: over 2 years ago - Pushed at: almost 3 years ago - Stars: 2 - Forks: 0

Sidessh/Multi-Class-Multi-Output-Classification

Multi - Output Multi-Class Classification problem, Job-Type, and Job-Category Prediction

Language: Jupyter Notebook - Size: 22.9 MB - Last synced at: about 2 years ago - Pushed at: about 3 years ago - Stars: 2 - Forks: 1

abduliante/vehicle-default-loan-prediction

Forecasting the likelihood of a customer defaulting their auto loan using classification models

Language: Python - Size: 69.7 MB - Last synced at: about 6 hours ago - Pushed at: over 3 years ago - Stars: 2 - Forks: 1

hanaecarrie/CS5228_kaggle_income50K_classification

CS5228 Kaggle Inclass Competition: Predicting if Income > 50K

Language: Jupyter Notebook - Size: 130 MB - Last synced at: over 2 years ago - Pushed at: over 4 years ago - Stars: 2 - Forks: 1

Naddour98/my-1st-project

My 1st data analysis project - Predicting Employee Turnover using ML models

Language: Jupyter Notebook - Size: 16.2 MB - Last synced at: 6 days ago - Pushed at: 6 days ago - Stars: 1 - Forks: 0

jibbs1703/Classic-ML-Models

This repository contains scripts for developing, training and evaluating machine learning models using several python frameworks.

Language: Jupyter Notebook - Size: 3.31 MB - Last synced at: 6 days ago - Pushed at: 7 days ago - Stars: 1 - Forks: 0

dpb24/fake-news-detector

Building a machine learning model to classify fake and real news using scikit-learn and XGBoost (Python)

Language: Jupyter Notebook - Size: 2 MB - Last synced at: 7 days ago - Pushed at: 8 days ago - Stars: 1 - Forks: 0

KKeshav1101/mini_project

A Django Application Interface for Hate Speech Detection Mini Project

Language: Python - Size: 334 KB - Last synced at: 9 days ago - Pushed at: 9 days ago - Stars: 1 - Forks: 1

Onome-Joseph/Customer-Churn-Prediction

This project predicts whether a customer is likely to stop patronizing a business by making use of historical customer data.

Language: Jupyter Notebook - Size: 1.53 MB - Last synced at: 11 days ago - Pushed at: 11 days ago - Stars: 1 - Forks: 0

aadhamashraf/Fraud-Detection-Interpretability-and-Explainability

Developing fraud detection systems using a variety of machine learning and deep learning models. Emphasis is placed on model explainability to ensure transparency in predictions, an essential aspect in financial applications.

Language: Jupyter Notebook - Size: 24.3 MB - Last synced at: 29 days ago - Pushed at: 29 days ago - Stars: 1 - Forks: 0

mahnoorsheikh16/Sketchify-A-Quick-Draw-drawing-classifier

Implementation of a sketch‐recognition pipeline inspired by Google’s Quick, Draw!—from raw stroke data to prediction. Includes data preprocessing and feature‐engineering scripts, three Bayesian classifiers alongside Logistic Regression, SVM, K-NN and XGBoost baselines, and an RNN model.

Language: Jupyter Notebook - Size: 6.11 MB - Last synced at: 29 days ago - Pushed at: 29 days ago - Stars: 1 - Forks: 0

mahnoorsheikh16/Credit-Card-Default-Prediction

This project focuses on predicting whether a customer will default on their credit card payment in the upcoming month. Utilizing historical transaction data and customer demographics, the project employs various machine learning algorithms to distinguish between risky and non-risky customers for better credit risk management.

Language: Jupyter Notebook - Size: 14.6 MB - Last synced at: 29 days ago - Pushed at: 29 days ago - Stars: 1 - Forks: 0

UsmanShaikh24/Machine-Learning-Model-For-Anomaly-Detection-and-Predictive-Maintenance

This project addresses the growing need for intelligent industrial maintenance systems. By applying machine learning techniques, we aim to detect anomalies in machine behavior, predict machine failures, estimate Remaining Useful Life (RUL), and schedule maintenance tasks based on priority—enhancing reliability and minimizing downtime.

Language: Jupyter Notebook - Size: 6.19 MB - Last synced at: 30 days ago - Pushed at: 30 days ago - Stars: 1 - Forks: 0

Ramtin-Karbaschi/Titanic_XGBOOSTmodel

XGBoost classification model predicting Titanic passenger survival with data preprocessing, feature engineering, and SMOTE for class balancing. Developed for the Kaggle Titanic competition.

Language: Jupyter Notebook - Size: 9.77 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 1 - Forks: 0

ankushmallick1100/Diabetes-Prediction-of-Females-using-Maching-Learning-Techniques

This is a machine learning work that uses various machine learning algorithms to predict whether a patient is diabetic or not. Here various machine learning algorithms like SVM, RF Classifier, DT Classifier, KNN, LR , LR with CV, NB Classifier, and XGB are used. For this work, a website is made with Python Streamlit library.

Language: Jupyter Notebook - Size: 105 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 1 - Forks: 0

andreas-pattichis/ML-for-RNA-Seq-Disease-Classification-and-Biomarker-Discovery

This project develops a machine learning model to classify individuals as healthy, having rheumatoid arthritis (RA), or systemic lupus erythematosus (SLE) using RNA-Seq gene expression data. The project also identifies significant genes as potential biomarkers, leveraging SGDClassifier and XGBoost models.

Language: Jupyter Notebook - Size: 2.27 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 1 - Forks: 0

IzaacCoding36/Projeto-ONIA

Esse repositório será utilizado para a publicação e desenvolvimento do meu projeto para a Olimpíada Nacional de Inteligência Artificial (ONIA) de 2025.

Language: Python - Size: 1.78 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 1 - Forks: 0

Shailesh-Padhariya/Human-Resources

This project analyzes employee attrition using machine learning models, including Logistic Regression, Random Forest, and XGBoost. The objective is to identify key factors influencing employee turnover and provide insights to improve retention strategies

Language: Jupyter Notebook - Size: 1.05 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 1 - Forks: 0

RamishFatimaa/Bank-Term-Deposit-Predictions

Predicting bank term deposit subscriptions using Gradient Boosting, feature importance analysis, and customer segmentation for targeted marketing.

Language: Python - Size: 2.13 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 1 - Forks: 0

Ali-EL-Badry/Machine-learning-Algorithm

It is a Repo that contain different type of Machine Learning Algorithm like Regression ,classification and clustering that will be added soon

Language: Jupyter Notebook - Size: 3.07 MB - Last synced at: 3 months ago - Pushed at: 4 months ago - Stars: 1 - Forks: 0

dariak153/All_NBA_Teams_Prediction

Prediction of players being selected to All-NBA 1st 2nd 3rd Teams and All-NBA Rookie 1st, 2nd Teams. For season 2023/24

Language: Jupyter Notebook - Size: 15.7 MB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 1 - Forks: 0

saob007/Modelado_retencion_personal_proyecto

Construcción de un modelo de aprendizaje automático que permite predecir si un empleado desertará o no de una empresa industrial de desarrollo automotriz

Language: Jupyter Notebook - Size: 18.2 MB - Last synced at: 3 months ago - Pushed at: 5 months ago - Stars: 1 - Forks: 0

Ansuman21/Analyzing-and-Forecasting-Restaurant-Inspection-Grades-in-NYC

Data Science Project (Final)

Language: Jupyter Notebook - Size: 71 MB - Last synced at: 5 months ago - Pushed at: 5 months ago - Stars: 1 - Forks: 0

Onome-Joseph/NBA-match-prediction

The model predicts whether a team will win or lose based on player performance statistics from the 2024/25 NBA season.

Language: Jupyter Notebook - Size: 690 KB - Last synced at: 2 months ago - Pushed at: 6 months ago - Stars: 1 - Forks: 0

Jesly-Joji/Money-Laundering-Classification

Money Laundering Classification on IBM Transactions

Language: Jupyter Notebook - Size: 412 KB - Last synced at: 3 months ago - Pushed at: 7 months ago - Stars: 1 - Forks: 0

LinaYorda/predicting-crime-with-machine-learning

This project explores the applicability of various machine learning models to predict whether a crime was solved, based on a comprehensive dataset from the USA for the period 1980-2014.

Language: Jupyter Notebook - Size: 2.55 MB - Last synced at: 7 months ago - Pushed at: 7 months ago - Stars: 1 - Forks: 0

tderick/android-malware-detection

This project aims to build an effective classification model to classify a mobile application as Benign or Malware. To do so, we'll evaluate multiple classification models using different metrics and select the best model with better performance for our dataset. Finally, we deployed our model as a REST API using FastAPI.

Language: Jupyter Notebook - Size: 5.55 MB - Last synced at: 3 months ago - Pushed at: 7 months ago - Stars: 1 - Forks: 0

yoihxn/MNIST-Digit-Classification-using-XGBoost

Using XGBoost on MNIST to classify Handwritten Digits

Language: Jupyter Notebook - Size: 1.15 MB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 1 - Forks: 0

johnsonhk88/Data-Science-Challenge-Coursera-Project-Loan-Default-Prediction

Data Science Challenge from Coursera Project : Loan Default Prediction

Language: Jupyter Notebook - Size: 13.7 MB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 1 - Forks: 0

mahnoorsheikh16/Loan-Default-Prediction

Credit risk is the borrower’s inability to repay a loan. Machine Learning models can predict risky customers and reduce lender losses. By analyzing behavior and demographics of past customers, these insights can apply to future customers for better loan decisions. This study aims to find the most suitable model for predicting loan defaults.

Language: Jupyter Notebook - Size: 2.38 MB - Last synced at: 21 days ago - Pushed at: 9 months ago - Stars: 1 - Forks: 0

varmatilak22/Credit_Score_Prediction

This project predicts credit scores ('Good', 'Standard', 'Poor') using a streamlined ML pipeline. It includes data extraction, cleaning, and preprocessing. Key techniques are Mutual Information for feature selection, PCA for dimensionality reduction, and XGBoost for accurate and efficient model training, ensuring reliable and robust predictions.

Language: HTML - Size: 5.57 MB - Last synced at: 9 months ago - Pushed at: 9 months ago - Stars: 1 - Forks: 0

AbhinavSharma07/Fraud_Analytics-Credit_Card_Fraud_Detection

The aim of this project is to predict fraudulent credit card transactions with the help of different machine learning models.

Language: Jupyter Notebook - Size: 3.39 MB - Last synced at: 3 months ago - Pushed at: 10 months ago - Stars: 1 - Forks: 0

Assem-ElQersh/Creativa-Data-Science-Bootcamp

Jupyter notebooks from the Creativa Data Science Bootcamp, covering key data science concepts and practices across multiple sessions, from data preprocessing to model building and time series analysis.

Language: Jupyter Notebook - Size: 1.17 MB - Last synced at: 3 months ago - Pushed at: 10 months ago - Stars: 1 - Forks: 0

Jayita11/Defaulter-Credit-Card-Prediction_ML

This project predicts credit card defaults using machine learning. The XGBoost model, optimized with under-sampling, was the best performer, effectively handling class imbalance and achieving strong recall and accuracy.

Language: Jupyter Notebook - Size: 27.1 MB - Last synced at: 3 months ago - Pushed at: 10 months ago - Stars: 1 - Forks: 1

gajendrasharma-github/Employee-Promotion-Prediction-Analytics

A Classification Project using F1_Score as the evaluation Metric

Language: Jupyter Notebook - Size: 1.65 MB - Last synced at: 3 months ago - Pushed at: 10 months ago - Stars: 1 - Forks: 0

Boudry-Felix/EIH_Classifier

Research work about modeling the EIH phenomenon.

Language: R - Size: 225 KB - Last synced at: 8 months ago - Pushed at: 11 months ago - Stars: 1 - Forks: 0

erickmonga09/Predicting_Internet_Gaming_Disorder_diagnosis

This is a repository of my data science thesis project, where I performed a comparative study to predict Internet Gaming Disorder (IGD) in gamers based on questionnaire data. More detail in the README file

Language: Jupyter Notebook - Size: 579 KB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 1 - Forks: 0

YazdanEtedali/SDN_DDoS_Detection_and_Mitigation_System

Artificial Intelligence and Cybersecurity

Language: Jupyter Notebook - Size: 2.33 MB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 1 - Forks: 0

dariak153/Comprasion_of_classifiers

The goal of this project was used advanced preprocessing and feature engineering. Achieved high accuracy with XGBoost and LightGBM. Deployed via a Django web application and visualization was presented using Dash and Plotly.

Language: Python - Size: 770 KB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 1 - Forks: 0

tanzealist/Disease-Prediction-Benchmarking

A comprehensive diagnostic pipeline that uses symptom data to predict diseases using state-of-the-art machine learning models like SVM and XGBoost.

Language: Jupyter Notebook - Size: 8.79 MB - Last synced at: 12 months ago - Pushed at: 12 months ago - Stars: 1 - Forks: 0

Owadd/Credit-Risk-Assessment

This project aims to predict credit risk for individuals applying for loans, classifying whether they will default based on features such as age, income, employment length, loan amount, interest rate, percentage of income, credit length, home ownership, and loan intent.

Language: Python - Size: 1.35 MB - Last synced at: 12 months ago - Pushed at: 12 months ago - Stars: 1 - Forks: 0

iamdebasishdas123/Spam_Email_Classifier

This model checks the email and classifies the email as spam or not.

Language: Jupyter Notebook - Size: 1.46 MB - Last synced at: 3 months ago - Pushed at: 12 months ago - Stars: 1 - Forks: 0

juliorodrigues07/url_detection

Malicious URL detector built with deep exploration on feature engineering.

Language: Python - Size: 144 MB - Last synced at: 12 months ago - Pushed at: 12 months ago - Stars: 1 - Forks: 0